# Do Social Media, Good Governance, and Public Trust Increase Citizens’ e-Government Participation? Dual Approach of PLS-SEM and fsQCA

Authors: Marlan Hutahaean; Ixora Javanisa Eunike; Andri Dayarana K. Silalahi
Journal: Human Behavior and Emerging Technologies
 (2023)

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## Abstract

Citizens’ participation in e-government is imperative for the government as it implies citizens’ participation in public policy. Furthermore, how government strategies allocate resources to increase participation in e-government is essential to investigate. Nevertheless, scant literature debates how e-government can facilitate citizen participation as part of the government’s deliberative policy-making process. To fill the gap, this study uses social media, good governance, and trust to predict e-government participation and testing the hypothesis using PLS-SEM and fsQCA on 455 Indonesian participants who have experience with e-government. The results from SEM confirmed that trust in e-government is the principal predictor of achieving citizens’ participation. To achieve citizens’ trust in e-government, the government must consider perceived ease of use and usefulness as critical factors while spreading e-government-related information on social media. At the same time, transparency from the good governance aspect enhances citizens’ trust. The results of fsQCA equip theoretical and practical insights for the government to determine whether citizens have high or low levels of e-government participation. In achieving high e-government participation, trust, information quality, perceived ease of use, and perceived usefulness are necessary. Besides, low participation occurs when information about e-government is absent on social media and do not care about good governance. These findings will assist the government in comprehensively improving public services through social media and good governance.


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## Body

## 1. Introduction

Information, communications, and technology (ICT) encourage the government to have the structures to perform public policies efficiently [1]. In Indonesia, the government considers ICT a crucial resource in operating public services since it can accommodate a wide range of services for the public in a relatively short time. Also, the increasing use of ICT in delivering public services to citizens caused it to become increasingly crucial to deliver government services. Though, execution effective public service using ICT continues to challenge the government [2]. This was identified by observing the high public demand for solving problems and fulfilling various public service interests.One of the ICT products, namely, e-government, was used by the government at that time to provide adequate services to the public [3]. The essence of e-government centers on the delivery of government services electronically [4]. e-Government can be implemented to improve information management systems and public service progressions and augment the use of information technology. The objective of e-government in the public sector is to provide information and services and build strategic relationships among the government, private sector, civil society organizations, and public [5]. As a result of e-government, the possibility of improving public trust in decision-making processes and creating policies, information, and services in cooperation with the government is enhanced. Due to the effective and efficient interaction between government and society, e-government plays a vigorous role in public policy [6].The United Nation survey in 2022 revealed that Indonesia is ranked 77th in the E-Government Development Index (EGDI) and has risen 11 ranks from 2021 [7]. Databox survey in year of 2022 reports that Indonesia ranks fifth in the Southeast Asia in terms of EGDI, with an index value of nearly 0.80 [8]. However, the government must recognize whether this corresponds to the quality of service the community feels they receive. Despite its ranking, e-government implementation could be more “fabulous.” Indonesia faces several impediments when implementing e-government. The following points are summarized: (1) transparency of the legal protection, (2) unclear mechanisms for implementation, and (3) limited IT support. Due to this, the public needs amplification about how e-government should be implemented, resulting in an ineffective deliberative approach in implementing public policy.e-Government research has discovered that good governance plays an imperative role in supporting the successful implementation of e-government [9]. Thus, in addition to its ICT components, good governance is essential because it will facilitate community participation through government performance concerning the enactment of e-government. Along with implementing e-government, the government can also increase public participation by implementing good governance principles [10]. Nevertheless, it is essential to investigate how to achieve a high level of public participation in e-government to expand public service efficiency. As noted in previous studies, e-government participation has amplified in a variety of practices, including electronic services, that support e-government participation (e.g., e-informing and e-consulting) [11], national culture [12], user awareness, experience, and access barriers [13], which are primarily intensive on user characteristics and technology awareness. A key achievement of the government in implementing public policy is e-government participation, which is not solely observed from the perspective of culture, user experience, and technology but also from the perspective of the government’s role in socializing the use of e-government through media exposure (e.g., social media) since it is favorably pledging to the public. Instead, implementing the principles of good governance by the government will increase public trust in the government when appropriately implemented.e-Government is one of the instruments to increase public participation in public policy. The increasing public participation in e-government shows the effectiveness of the implementation of policy instruments. Deliberative policy theory asserts that the participation of a diverse range of stakeholders in a public policy is essential to its effectiveness. Several stakeholders, including the community, will have to gain their trust for this to be possible. Mah et al. [14] have developed a model for achieving deliberative policy-making based on the element of trust, demonstrating that trust plays a significant role in the application of government policies. It is challenging to achieve citizens’ trust in government practice [15, 16]. Therefore, exploring ways to increase trust in the e-government as a deliberative policy implementation tool is essential. The government faces a new challenge in increasing public trust. Especially in today’s technological age, it becomes a dilemma for the government to use social media as an effective medium for socializing e-government [17]. Due to its exposure, it can create a variability of perceptions about the government among the general public. There is increasing negative information about the government on social media, making it gradually problematic to cultivate a positive impression of e-government socialization that will increase community participation. A lack of good governance in the administration of e-government will be a predictor that citizen will not be able to participate actively. Mansoor [18] suggests that good governance in implementing e-government policies determines public trust in government policies. As a result, this study identified gaps in the implementation of e-government as an instrument of government policy to achieve deliberative policy-making through considerations such as social media, good governance, and trust.To fill the gap in literature, this study recommends a model of e-government participation using the principles of deliberative policy and incorporating social media, good governance, and trust into a model predicting e-government participation. This is based on the following reasons: (1) social media elements are observed as significant in outreach and increasing e-government management transparency to the public. Thus, public trust in the government and the e-government system is increasing. According to Mansoor [18], social media has become increasingly crucial for the government in communicating policies due to increased public trust. (2) Good governance can be understood as a combination of accountability, responsiveness, and responsibility. Mostly, the three principles of good governance are vital for the government in operating their administration, including implementing them in e-government policies. According to Beshi and Kaur [19], transparency and accountability in government operations and policies will increase public trust, which can facilitate the growth of e-government. (3) Trust is critical for the government to support public participation in every public policy [20]. Consequently, when public trust in government policies and programs regarding e-government increases, community participation in these programs will increase. In order to predict e-government participation, the three elements of social media, good governance, and trust are incorporated into a deliberative policy-based model. In addition, this study uses a dual analysis approach of structural equation modeling (SEM) and fuzzy set qualitative comparative analysis (fsQCA) as a methodological contribution. As part of the research, SEM analysis will be used to test research models and hypotheses. Meanwhile, fsQCA analysis is utilized to advance configurations for e-government participation. Thus, the management in e-government practices will be furnished with respective configurations to achieve “high” participation and avoiding “low” participation. Additionally, the following section discusses the literature review, methods, results, theoretical contributions, and e-government practices in more detail.


## 2. Literature Review and Hypothesis Development

### 2.1. Deliberative Policy Theory

Deliberative policy theory is derived from a practice known as “deliberative planning” [21]. Deliberative planning is a method for addressing complex public sector issues [22]. Initially, this theory was considered an alternative to standard empirical, analytical methods for solving public policy problems [23]. However, this method is limited in that it cannot provide concrete results that will influence the implementation of public policies. Wagenaar and Cook [24] provide a fundamental understanding of public policy practices in modern societies by highlighting three aspects of policy, namely, interpretative, moral (pragmatic), and emotional (linguistic). As a result of these three aspects, government interaction with the public is improved.A deliberative policy involves community planning policy-making by inviting the community to participate actively in discussing and considering public policy values [25]. As one of the stakeholders, communities will have the opportunity to identify, evaluate, and discuss the relevance of public policies to the existing conditions of society in a deliberative manner [26]. Additionally, the community can communicate its opinions regarding a policy to the government through discussion activities. The government responds to this view as a means of being inclusive and involving the active participation of the community in policy development. In this way, the government and the community can collaborate on policy-making to address dynamic challenges within contemporary society [24, 27]. As a result, there is a cooperative and communicative solution to the commitment to implement democracy through deliberative policies [28].Technological media (e.g., social media) significantly delivers public services [29]. Social media is mainly used to increase public policy-making participation [30]. In order to increase the effectiveness and efficiency of public services through social media, this research will examine various aspects of encouraging public participation and implementing e-government as public policy. According to Todisco et al. [29], social media can affect public perceptions of policy-making processes and service quality. Social media also provides a high level of interactive access to information for policy-making by interacting with the government and society directly. This allows for a complex, relational, and practical formulation of public policy regarding e-government [31].A significant purpose of e-government is to provide information and services and exchange knowledge and information. Increasing interaction, participation, and collaboration is intended to facilitate collective decision-making regarding the public interest [1]. e-Government policy has evolved from utilizing traditional media to utilizing applications. In addition to providing services related to filing requests, such as applications for business licenses, licenses, electronic identification, and electronic key tokens, the e-government application also provides services related to filing requests. Additionally, utilities (e.g., electricity, gas, and telephone), fines, and tax returns can be paid online [32]. Additionally, this online service offers the opportunity for the public to be more active in the administration of public [1]. Consequently, the public can collaborate in making public policy decisions by observing how the government takes action. Thus, the community can become a supervisor by observing the government’s actions.


### 2.2. e-Government Participation

e-Government is a complex phenomenon that depends heavily on information and communication technologies (ICT). According to Yang and Rho [33], e-government is about improving government efficiency, service quality, and democratic participation. Using e-government to access relevant information, conduct electronic transactions with the government, and participate in government decision-making is an objective [34]. Additionally, e-government is used for transactional purposes, information seeking, decision-making, and creating policies, services, and information in collaboration with the government. Public policy relies heavily on e-government since it enables effective and efficient interaction between the government and the community [6].The published literature indicates that e-government can increase the effectiveness of government-community interaction. Traditional transactions, participation, and management are associated with it. Seo et al. [35] found that only a few people used e-government and that most prefer traditional services. Consequently, citizens cannot always participate in decision-making processes [36]. The implementation of e-government is also hindered by insufficient infrastructure, transparency, and effective human resource management [2, 35]. The public disregards government policies and actions because of these obstacles [37, 38]. As a result, trust and participation can be increased by implementing e-government services. In order to improve public services [39], e-government is one of the newest management movements designed to increase community trust and active participation.According to Nam [6] and Khan et al. [40], e-government participation is the concept that describes citizens’ behavior formed after believing in e-government participation, where they interact and participate in decision-making processes related to public policies. A key benefit of e-government is promoting citizen participation, an effective method of improving government-community relations [40]. As a strategy for enhancing participation in social media and good governance, the government provides e-government services. Social media makes it easier for people to access information and utilize e-government services for convenience, needs, and community benefits. Hence, social media can enhance information quality [41], perceived ease of use [40], and perceived usefulness [42]. It is also possible to build trust through transparent, accountable, and responsive public services [43]. Thus, social media factors and good governance will promote trust in e-government [39].


### 2.3. Trust

Individuals can develop a sense of trust by establishing positive expectations concerning the intentions and behavior of their trust object [44]. According to Khan et al. [40], trust to e-government refers to the extent to which citizens understand the risk and uncertainty associated with using government so that they can rely on and trust e-government. In this study, e-government, as the object of trust, plays a vital role in converting the factors that form trust into trust-related outputs, namely, participation. Participation in e-government is expected to be influenced by positive expectations of trust in e-government. Khan et al. [40] assert that trust reduces risk and uncertainty. Therefore, predictor trust suggests that the public understands the risks and uncertainties associated with using e-government. Khan et al. [40] propose that trust can facilitate community participation through electronic government. Thus, this study proposes the following hypothesis.H1. When citizens trust to e-government, it will likely increase their participation.


### 2.4. Social Media

The use of social media as part of e-government facilitates interaction between government and society [45]. Hung et al. [46] examine how social media affects perceived usefulness, ease of use, and information quality in e-government. Regarding e-government in social media, information quality is essential, particularly when citizens seek information and other users’ experiences using e-government on social media. Lee and Levy [47] and Khan et al. [40] defined information quality as public perception about e-government sources of information that are accurate, complete, relevant, up-to-date, and valuable according to the community’s needs. Lee and Levy [47] argue that information content is geared toward those primarily responsible for e-government usage. Citizens perceive e-government as reliable when it is comprehensive and accurate [48]. Therefore, information quality fosters trust in e-government implementation and success [39]. Accordingly, the hypothesis is as follows.H2a. Information quality of e-government on social media will likely increase citizens’ trust.Citizens consider e-government information on social media easy to access and utilize without constraints [49, 50]. According to Davis [49] and Khan et al. [40], perceived ease of use refers to the extent to which citizens believe that e-government information is flexible and easy to use without any constraints. In other words, when e-government information is available easily and flexibly and is easy to find via social media, it can affect the ease of use. According to previous study, the availability and flexibility of e-government information on social media can affect trust [40]. When e-government information is easily accessible, more people will be willing to utilize it, increasing trust [40, 51]. As a result, the following hypothesis is proposed.H2b. Perceived ease of use of e-government on social media will likely increase citizens’ trust.Social media is increasingly becoming a platform for citizens to mobilize valuable information about e-government. According to Davis [49] and Chen and Aklikokou [42], perceived usefulness refers to the extent to which citizens believe that using e-government information on social media can improve effectiveness and performance and benefit the community. e-Government information is perceived to be valuable by citizens to the degree that they believe it will improve their understanding and needs [49, 50]. As e-government becomes easier to use, the public will benefit more from it [52]. A perceived usefulness assessment is based on the effectiveness and usefulness of information perceived by the public regarding e-government [53]. Accordingly, when information is considered valuable, this will increase public trust [51]. Therefore, the hypothesis that can be proposed is as follows.H2c. Perceived usefulness of e-government on social media will likely increase citizens’ trust.


### 2.5. Good Governance

To enhance the state’s capabilities, it must create institutions limiting its ability to commit fraudulent acts [54]. e-Government will strengthen, stabilize, and expand democracy, and citizens will have access to public policy information. Governments must achieve this goal to improve public service quality. Accordingly, the concept of governance and trust suggests that the government should pay close attention to governance issues such as transparency, accountability, and responsiveness [18, 55].Sabani [2] defined transparency as to the availability of relevant information regarding government performance procedures and public policy decision-making processes that are implemented transparently to the public. Therefore, it is essential to consider that the decision-making process and performance procedures are transparent to the public [2]. This information assists the public in better understanding the government [56]. Information includes complete and relevant public service activities, including operational guidelines for the use of e-government, government budgets, and government expenditures [2]. Consistent and comprehensive communication of government performance information will increase public trust. Transparency, a conventional issue, must be implemented to increase trust in e-government [18, 57]. As a result, the following hypothesis may be proposed.H3a. The citizens’ perceived government’s transparency will likely increase trust to e-government.Good governance is associated with many values, including accountability, which is viewed by many as a government obligation. According to Al-Shbail and Aman [58], accountability refers to the extent to which the government is responsible for its decisions and actions towards the community to achieve e-government program implementation performance. As a result, the government is responsible for implementing policies effectively, efficiently, and economically for the community [58]. A positive channel for accountable government is the use of e-government as a means to foster public trust [18]. Beshi and Kaur [19] indicate that a critical advantage of e-government is enhancing accountability within the government. This, in turn, increases public trust. The following hypothesis may be formulated.H3b. The citizens’ perceived government’s accountability will likely increase trust to e-government.As a critical component of community involvement through social media-based e-government, responsiveness is crucial [59]. According to Mansoor [18], responsiveness assures that the government cares about the suggestions, opinions, and demands of the community in improving the quality of e-government services. As part of this appraisal, citizens care about the rapidity with which e-government information responds to community recommendations, opinions, and demands [18]. When citizens communicate their aspirations and needs through e-government, they expect a fast and effective response from the government [60]. The ability of the government to respond appropriately to the aspirations and requests of the community and to provide efficient feedback will increase trust in e-government [18, 19].H3c. The citizens’ perceived government’s responsiveness will likely increase trust to e-government.


## 2.1. Deliberative Policy Theory

Deliberative policy theory is derived from a practice known as “deliberative planning” [21]. Deliberative planning is a method for addressing complex public sector issues [22]. Initially, this theory was considered an alternative to standard empirical, analytical methods for solving public policy problems [23]. However, this method is limited in that it cannot provide concrete results that will influence the implementation of public policies. Wagenaar and Cook [24] provide a fundamental understanding of public policy practices in modern societies by highlighting three aspects of policy, namely, interpretative, moral (pragmatic), and emotional (linguistic). As a result of these three aspects, government interaction with the public is improved.A deliberative policy involves community planning policy-making by inviting the community to participate actively in discussing and considering public policy values [25]. As one of the stakeholders, communities will have the opportunity to identify, evaluate, and discuss the relevance of public policies to the existing conditions of society in a deliberative manner [26]. Additionally, the community can communicate its opinions regarding a policy to the government through discussion activities. The government responds to this view as a means of being inclusive and involving the active participation of the community in policy development. In this way, the government and the community can collaborate on policy-making to address dynamic challenges within contemporary society [24, 27]. As a result, there is a cooperative and communicative solution to the commitment to implement democracy through deliberative policies [28].Technological media (e.g., social media) significantly delivers public services [29]. Social media is mainly used to increase public policy-making participation [30]. In order to increase the effectiveness and efficiency of public services through social media, this research will examine various aspects of encouraging public participation and implementing e-government as public policy. According to Todisco et al. [29], social media can affect public perceptions of policy-making processes and service quality. Social media also provides a high level of interactive access to information for policy-making by interacting with the government and society directly. This allows for a complex, relational, and practical formulation of public policy regarding e-government [31].A significant purpose of e-government is to provide information and services and exchange knowledge and information. Increasing interaction, participation, and collaboration is intended to facilitate collective decision-making regarding the public interest [1]. e-Government policy has evolved from utilizing traditional media to utilizing applications. In addition to providing services related to filing requests, such as applications for business licenses, licenses, electronic identification, and electronic key tokens, the e-government application also provides services related to filing requests. Additionally, utilities (e.g., electricity, gas, and telephone), fines, and tax returns can be paid online [32]. Additionally, this online service offers the opportunity for the public to be more active in the administration of public [1]. Consequently, the public can collaborate in making public policy decisions by observing how the government takes action. Thus, the community can become a supervisor by observing the government’s actions.


## 2.2. e-Government Participation

e-Government is a complex phenomenon that depends heavily on information and communication technologies (ICT). According to Yang and Rho [33], e-government is about improving government efficiency, service quality, and democratic participation. Using e-government to access relevant information, conduct electronic transactions with the government, and participate in government decision-making is an objective [34]. Additionally, e-government is used for transactional purposes, information seeking, decision-making, and creating policies, services, and information in collaboration with the government. Public policy relies heavily on e-government since it enables effective and efficient interaction between the government and the community [6].The published literature indicates that e-government can increase the effectiveness of government-community interaction. Traditional transactions, participation, and management are associated with it. Seo et al. [35] found that only a few people used e-government and that most prefer traditional services. Consequently, citizens cannot always participate in decision-making processes [36]. The implementation of e-government is also hindered by insufficient infrastructure, transparency, and effective human resource management [2, 35]. The public disregards government policies and actions because of these obstacles [37, 38]. As a result, trust and participation can be increased by implementing e-government services. In order to improve public services [39], e-government is one of the newest management movements designed to increase community trust and active participation.According to Nam [6] and Khan et al. [40], e-government participation is the concept that describes citizens’ behavior formed after believing in e-government participation, where they interact and participate in decision-making processes related to public policies. A key benefit of e-government is promoting citizen participation, an effective method of improving government-community relations [40]. As a strategy for enhancing participation in social media and good governance, the government provides e-government services. Social media makes it easier for people to access information and utilize e-government services for convenience, needs, and community benefits. Hence, social media can enhance information quality [41], perceived ease of use [40], and perceived usefulness [42]. It is also possible to build trust through transparent, accountable, and responsive public services [43]. Thus, social media factors and good governance will promote trust in e-government [39].


## 2.3. Trust

Individuals can develop a sense of trust by establishing positive expectations concerning the intentions and behavior of their trust object [44]. According to Khan et al. [40], trust to e-government refers to the extent to which citizens understand the risk and uncertainty associated with using government so that they can rely on and trust e-government. In this study, e-government, as the object of trust, plays a vital role in converting the factors that form trust into trust-related outputs, namely, participation. Participation in e-government is expected to be influenced by positive expectations of trust in e-government. Khan et al. [40] assert that trust reduces risk and uncertainty. Therefore, predictor trust suggests that the public understands the risks and uncertainties associated with using e-government. Khan et al. [40] propose that trust can facilitate community participation through electronic government. Thus, this study proposes the following hypothesis.H1. When citizens trust to e-government, it will likely increase their participation.


## 2.4. Social Media

The use of social media as part of e-government facilitates interaction between government and society [45]. Hung et al. [46] examine how social media affects perceived usefulness, ease of use, and information quality in e-government. Regarding e-government in social media, information quality is essential, particularly when citizens seek information and other users’ experiences using e-government on social media. Lee and Levy [47] and Khan et al. [40] defined information quality as public perception about e-government sources of information that are accurate, complete, relevant, up-to-date, and valuable according to the community’s needs. Lee and Levy [47] argue that information content is geared toward those primarily responsible for e-government usage. Citizens perceive e-government as reliable when it is comprehensive and accurate [48]. Therefore, information quality fosters trust in e-government implementation and success [39]. Accordingly, the hypothesis is as follows.H2a. Information quality of e-government on social media will likely increase citizens’ trust.Citizens consider e-government information on social media easy to access and utilize without constraints [49, 50]. According to Davis [49] and Khan et al. [40], perceived ease of use refers to the extent to which citizens believe that e-government information is flexible and easy to use without any constraints. In other words, when e-government information is available easily and flexibly and is easy to find via social media, it can affect the ease of use. According to previous study, the availability and flexibility of e-government information on social media can affect trust [40]. When e-government information is easily accessible, more people will be willing to utilize it, increasing trust [40, 51]. As a result, the following hypothesis is proposed.H2b. Perceived ease of use of e-government on social media will likely increase citizens’ trust.Social media is increasingly becoming a platform for citizens to mobilize valuable information about e-government. According to Davis [49] and Chen and Aklikokou [42], perceived usefulness refers to the extent to which citizens believe that using e-government information on social media can improve effectiveness and performance and benefit the community. e-Government information is perceived to be valuable by citizens to the degree that they believe it will improve their understanding and needs [49, 50]. As e-government becomes easier to use, the public will benefit more from it [52]. A perceived usefulness assessment is based on the effectiveness and usefulness of information perceived by the public regarding e-government [53]. Accordingly, when information is considered valuable, this will increase public trust [51]. Therefore, the hypothesis that can be proposed is as follows.H2c. Perceived usefulness of e-government on social media will likely increase citizens’ trust.


## 2.5. Good Governance

To enhance the state’s capabilities, it must create institutions limiting its ability to commit fraudulent acts [54]. e-Government will strengthen, stabilize, and expand democracy, and citizens will have access to public policy information. Governments must achieve this goal to improve public service quality. Accordingly, the concept of governance and trust suggests that the government should pay close attention to governance issues such as transparency, accountability, and responsiveness [18, 55].Sabani [2] defined transparency as to the availability of relevant information regarding government performance procedures and public policy decision-making processes that are implemented transparently to the public. Therefore, it is essential to consider that the decision-making process and performance procedures are transparent to the public [2]. This information assists the public in better understanding the government [56]. Information includes complete and relevant public service activities, including operational guidelines for the use of e-government, government budgets, and government expenditures [2]. Consistent and comprehensive communication of government performance information will increase public trust. Transparency, a conventional issue, must be implemented to increase trust in e-government [18, 57]. As a result, the following hypothesis may be proposed.H3a. The citizens’ perceived government’s transparency will likely increase trust to e-government.Good governance is associated with many values, including accountability, which is viewed by many as a government obligation. According to Al-Shbail and Aman [58], accountability refers to the extent to which the government is responsible for its decisions and actions towards the community to achieve e-government program implementation performance. As a result, the government is responsible for implementing policies effectively, efficiently, and economically for the community [58]. A positive channel for accountable government is the use of e-government as a means to foster public trust [18]. Beshi and Kaur [19] indicate that a critical advantage of e-government is enhancing accountability within the government. This, in turn, increases public trust. The following hypothesis may be formulated.H3b. The citizens’ perceived government’s accountability will likely increase trust to e-government.As a critical component of community involvement through social media-based e-government, responsiveness is crucial [59]. According to Mansoor [18], responsiveness assures that the government cares about the suggestions, opinions, and demands of the community in improving the quality of e-government services. As part of this appraisal, citizens care about the rapidity with which e-government information responds to community recommendations, opinions, and demands [18]. When citizens communicate their aspirations and needs through e-government, they expect a fast and effective response from the government [60]. The ability of the government to respond appropriately to the aspirations and requests of the community and to provide efficient feedback will increase trust in e-government [18, 19].H3c. The citizens’ perceived government’s responsiveness will likely increase trust to e-government.


## 3. Research Model

According to deliberative policy theory, which will be examined in further detail, e-government services are the government’s strategy for increasing public participation through social media and good governance. This study is aimed at examining how e-government can be an object of trust that contributes significantly to the conversion of the factor of forming trust into an outcome of trust, namely, participation. As a result, this study examines how trust in e-government affects participation in the e-government system. Social media has affected public perceptions of policy-making and public services by fostering trust. The information quality, ease of use, and usefulness of social media are considered by analyzing e-government information on public trust [40, 51]. Public trust is enhanced by good governance based on transparency, accountability, and responsiveness [18, 19]. As a result, Figure 1 shows that social media and good governance can be combined to increase public trust in predicting participation.Figure 1
Proposed conceptual model predicting e-government participation.It was Anthony [21] who introduced the deliberative policy theory. However, Wagenaar and Cook [24] emphasized the development of new public policy practices in social media-based contemporary societies. As a public policy, e-government can improve the efficiency and effectiveness of public service. The social media-based deliberative approach is implemented through e-government. In order to increase public participation, e-government services can use social media and good governance. Lee and Levy [47] have found that people will use e-government information based on quality, ease of use, and usefulness [40, 51]. To effectively meet the needs of the public, the government must be transparent, accountable, and responsive. Consequently, these two factors drive public confidence in e-government [18, 19]. Trust is crucial to promote citizen participation through e-government [40]. This study indicates that e-government plays a significant role in converting factors that form a trust to the output of trust, which is participation. Positive expectations will translate into behavior, namely, participation, resulting from trust in e-government. This study is aimed at identifying different configurations that can lead to high or low participation through casual sequences by comparing social media and good governance. This study considers trust to be a distinctive and unique element. Figure 2 shows the research prepositions formed as follows.P1. The presence of single constructs of social media, good governance, and trust is not sufficient to cause high citizens’ participation to e-government.P2. The absence of single constructs of social media, good governance, and trust is not sufficient to cause low citizens’ participation to e-government.Figure 2
Illustration of asymmetrical model.


## 4. Research Method

### 4.1. Measures

This study uses measurement items according to previous studies summarized in Table1. The following is a detailed description of construct operationalization.Table 1
Table of measurement items.
ConstructCodeMeasurement itemsInformation qualityIQ1I believe the government has provide accurate information of e-government through social media.IQ2The government has provide an up-to-date information about e-government through social media.IQ3∗I believe the government has provide the information meets to my needs about e-government through social media.∗IQ4The government has provide relevant information about e-government through social media.IQ5The government has provide information about e-government which easy to understand.Perceived ease of usePEOU1Most of the e-government service information provided by government is easy to use.PEOU2I believe learning to use e-government from social media is easy.PEOU3I find social media as a flexible way of promoting strong relationships between citizens’ and e-government.PEOU4My interaction with government through social media about the use of e-government services would be clear and understandable.PEOU5It would be easy for me to become skillful in using e-government services through social media.Perceived usefulnessPU1Using social media regarding government services can improve the service quality that I will receive about e-government.PU2Using social media is increasing my effectiveness about e-government.PU3∗The use of social media can improve my performance to exchange information about e-government.∗PU4Generally, I find it useful to use information about e-government on social media.TransparencyTR1The government plan and program about e-government are implemented transparently.TR2The entire process of plan and program about e-government is transparently disclosed.TR3The public can clearly see the progress and situations of the administration e-government.TR4The government discloses sufficient information to the public about its performance implementing e-government.AccountabilityAT1The government has a regular reporting the achievements and results of the program against its objectives implementing e-government.AT2The government recognizes its responsibility toward the public through implementing e-government program.AT3The government abides by regulations in all circumstances in implementing e-government programs.AT4The government ensures proper usage of its budget in an authorized performance in implementing e-government programs.ResponsivenessRV1The government is sensitive to public opinions about e-government.RV2The government responds to public needs about e-government quickly.RV3∗The government is making sincere effort to support citizens who need help about e-government.∗RV4The government is efficient in providing quality solutions for public needs about e-government.RV5Citizen’s appeals to the government about e-government are treated properly within a reasonable period of time.Trust to e-governmentTTE1I trust this e-government.TTE2This e-government is a reliable to carry out public services.TTE3When it comes to do public services this e-government is trustworthy.e-Government participationEP1I intend to participate with e-government.EP2To participate with e-government is something that I would do.EP3I would use e-government information and services.EP4I predict I will participate with e-government in the future.EP5I would not hesitate to engage with e-government.Notes:∗ represents removed items.


#### 4.1.1. Information Quality

Lee and Levy [47] and Khan et al. [40] defined information quality as public perception about e-government sources of information that are accurate, complete, relevant, up-to-date, and valuable according to the community’s needs. The measurement items for construct information quality follow that of Khan et al. [40], and the developed five items include the following: (1) I believe the government has provided accurate information of e-government through social media; (2) the government has provided an up-to-date information about e-government through social media; (3) I believe the government has provided the information meets to my needs about e-government through social media; (4) the government has provided relevant information about e-government through social media; and (5) the government has provided information about e-government which is easy to understand. The items of information quality are measured with a 7-Likert scale ranging from 1=strongly disagree to 7=strongly agree.


#### 4.1.2. Perceived Ease of Use

According to Davis [49] and Khan et al. [40], perceived ease of use refers to the extent to which citizens believe that e-government information is flexible and easy to use without any constraints. The measurement items for construct perceived ease of use follow that of Khan et al. [40], and the developed five items include the following: (1) most of the e-government service information provided by government is easy to use; (2) I believe learning to use e-government from social media is easy; (3) I find social media as a flexible way of promoting strong relationships between citizens’ and e-government; (4) my interaction with government through social media about the use of e-government services would be clear and understandable; and (5) it would be easy for me to become skillful in using e-government services through social media. The items of perceived ease of use are measured with a 7-Likert scale ranging from 1=strongly disagree to 7=strongly agree.


#### 4.1.3. Perceived Usefulness

Davis [49] and Chen and Aklikokou [42] defined perceived usefulness as to which citizens believe that using e-government information can improve effectiveness and performance and benefit the community. The study developed four measures based on Khan et al. [40] measurement items, including (1) using social media regarding government services can improve the service quality that I will receive about e-government; (2) using social media is increasing my effectiveness about e-government; (3) the use of social media can improve my performance to exchange information about e-government; and (4) generally, I find it useful to use information about e-government on social media. Perceived usefulness is measured on a 7-Likert scale ranging from 1=strongly disagree to 7=strongly agree.


#### 4.1.4. Transparency

López-López et al. [61] and Sabani [2] defined transparency as to the availability of relevant information regarding government performance procedures and public policy decision-making processes that are implemented transparently to the public. Based on Hartanto et al. [62] measurement items, four measures were developed, including (1) the government plan and program about e-government are implemented transparently; (2) the entire process of plan and program about e-government is transparently disclosed; (3) the public can clearly see the progress and situations of the administration e-government; and (4) the government discloses sufficient information to the public about its performance implementing e-government. Transparency is measured on a 7-point Likert scale, where 1 indicates strongly disagree and 7 indicates strongly agree.


#### 4.1.5. Accountability

According to Al-Shbail and Aman [58], accountability refers to the extent to which the government is responsible for its decisions and actions towards the community to achieve e-government program implementation performance. This study develops four items to measure accountability based on Hartanto et al. [62] including (1) the government has a regular reporting the achievements and results of the program against its objectives implementing e-government; (2) the government recognizes its responsibility toward the public through implementing e-government program; (3) the government abides by regulations in all circumstances in implementing e-government programs; and (4) the government ensures proper usage of its budget in an authorized performance in implementing e-government programs. We measure accountability on a 7-point Likert scale, where 1 indicates strongly disagree and 7 indicates strongly agree.


#### 4.1.6. Responsiveness

According to Mansoor [18], responsiveness assures that the government cares about the suggestions, opinions, and demands of the community in improving the quality of e-government services. Based on Hartanto et al. [62], this study developed five responsiveness measures including (1) the government is sensitive to public opinions about e-government; (2) the government responds to public needs about e-government quickly; (3) the government is making sincere effort to support citizens who need help about e-government; (4) the government is efficient in providing quality solutions for public needs about e-government; and (5) citizen’s appeals to the government about e-government are treated properly within a reasonable period of time. Responsiveness is measured on a 7-Likert scale ranging from 1=strongly disagree to 7=strongly agree.


#### 4.1.7. Trust to e-Government

According to Khan et al. [40], trust to e-government refers to the extent to which citizens understand the risk and uncertainty associated with using government so that they can rely on and trust e-government. According to Belanche et al. [63], this study develops three accountability measures including (1) I trust this e-government; (2) this e-government is reliable to carry out public services; and (3) when it comes to do public services, this e-government is trustworthy. Trust to e-government is measured on a 7-Likert scale ranging from 1=strongly disagree to 7=strongly agree.


#### 4.1.8. e-Government Participation

According to Nam [6] and Khan et al. [40], e-government participation is the concept that describes citizens’ behavior formed after believing in e-government participation, where they interact and participate in decision-making processes related to public policies. This study develops five-item e-government participation according to Khan et al. [40] including (1) I intend to participate with e-government; (2) to participate with e-government is something that I would do; (3) I would use e-government information and services; (4) I predict I will participate with e-government in the future; and (5) I would not hesitate to engage with e-government. e-Government participation is measured on a 7-Likert scale ranging from 1=strongly disagree to 7=strongly agree.


### 4.2. Sampling Technique and Data Collection Procedure

In this study, research participants were selected using a purposive and a nonprobability sampling method. This survey targets a specific population and protects respondents’ privacy; therefore, we used an online survey to collect data. The research questionnaire includes two initial questions to ensure that respondents are aware of e-government information and implementation in Indonesia. Participants will be asked to confirm that they are familiar with government social media (e.g., Instagram, YouTube, and Facebook) and that they participate in discussions regarding the implementation of e-government in Indonesia through online media and the surrounding community. When a respondent answers “yes” to the two initial questions, he is qualified to produce consistent responses. This study collected respondent data using a Google Forms questionnaire distributed randomly through social media platforms (e.g., Instagram, WhatsApp, and Facebook). Previous studies also used the same data collection procedure [64, 65].


### 4.3. Analysis Techniques

In this study, two analysis approaches are used to test the data. First, structural equation modeling (SEM) will examine the causal relationship between variables. SEM analysis can be performed using SmartPLS 3.0 software. The measurement model is initially evaluated for convergent validity utilizing average variance extracted, composite reliability, and Cronbach’s alpha values for internal consistency [66]. Next, this study examined discriminant validity with the Fornell-Larcker criterion, heterotrait-monotrait (HTMT), and matrix cross-loading [67, 68]. To evaluate structural model strength explained by the endogenous constructs, this study follows Falk and Miller’s [69] R-square value (R2) to indicate the structural model’s strength.The second method of qualitative comparative analysis is fuzzy set qualitative comparative analysis (fsQCA), which tests propositions and determines whether the research model has asymmetrical relationships. A fsQCA test contributes to the development of theoretical and practical guidance by examining the theory’s complexity and its variables’ interdependence. A fsQCA analysis involves the following steps. The first step in the fsQCA test is calibration selection, which transforms 7-Likert scales into fuzzy data sets, such as “2” for nonmembership, “6” for membership, and “4” for the intersection [70]. A truth table is used to arrange the scores obtained and analyze them in light of the causal conditions of the independent variables. Based on the findings of this analysis, fsQCA was conducted to identify the most efficient and unique solution [70].


## 4.1. Measures

This study uses measurement items according to previous studies summarized in Table1. The following is a detailed description of construct operationalization.Table 1
Table of measurement items.
ConstructCodeMeasurement itemsInformation qualityIQ1I believe the government has provide accurate information of e-government through social media.IQ2The government has provide an up-to-date information about e-government through social media.IQ3∗I believe the government has provide the information meets to my needs about e-government through social media.∗IQ4The government has provide relevant information about e-government through social media.IQ5The government has provide information about e-government which easy to understand.Perceived ease of usePEOU1Most of the e-government service information provided by government is easy to use.PEOU2I believe learning to use e-government from social media is easy.PEOU3I find social media as a flexible way of promoting strong relationships between citizens’ and e-government.PEOU4My interaction with government through social media about the use of e-government services would be clear and understandable.PEOU5It would be easy for me to become skillful in using e-government services through social media.Perceived usefulnessPU1Using social media regarding government services can improve the service quality that I will receive about e-government.PU2Using social media is increasing my effectiveness about e-government.PU3∗The use of social media can improve my performance to exchange information about e-government.∗PU4Generally, I find it useful to use information about e-government on social media.TransparencyTR1The government plan and program about e-government are implemented transparently.TR2The entire process of plan and program about e-government is transparently disclosed.TR3The public can clearly see the progress and situations of the administration e-government.TR4The government discloses sufficient information to the public about its performance implementing e-government.AccountabilityAT1The government has a regular reporting the achievements and results of the program against its objectives implementing e-government.AT2The government recognizes its responsibility toward the public through implementing e-government program.AT3The government abides by regulations in all circumstances in implementing e-government programs.AT4The government ensures proper usage of its budget in an authorized performance in implementing e-government programs.ResponsivenessRV1The government is sensitive to public opinions about e-government.RV2The government responds to public needs about e-government quickly.RV3∗The government is making sincere effort to support citizens who need help about e-government.∗RV4The government is efficient in providing quality solutions for public needs about e-government.RV5Citizen’s appeals to the government about e-government are treated properly within a reasonable period of time.Trust to e-governmentTTE1I trust this e-government.TTE2This e-government is a reliable to carry out public services.TTE3When it comes to do public services this e-government is trustworthy.e-Government participationEP1I intend to participate with e-government.EP2To participate with e-government is something that I would do.EP3I would use e-government information and services.EP4I predict I will participate with e-government in the future.EP5I would not hesitate to engage with e-government.Notes:∗ represents removed items.


### 4.1.1. Information Quality

Lee and Levy [47] and Khan et al. [40] defined information quality as public perception about e-government sources of information that are accurate, complete, relevant, up-to-date, and valuable according to the community’s needs. The measurement items for construct information quality follow that of Khan et al. [40], and the developed five items include the following: (1) I believe the government has provided accurate information of e-government through social media; (2) the government has provided an up-to-date information about e-government through social media; (3) I believe the government has provided the information meets to my needs about e-government through social media; (4) the government has provided relevant information about e-government through social media; and (5) the government has provided information about e-government which is easy to understand. The items of information quality are measured with a 7-Likert scale ranging from 1=strongly disagree to 7=strongly agree.


### 4.1.2. Perceived Ease of Use

According to Davis [49] and Khan et al. [40], perceived ease of use refers to the extent to which citizens believe that e-government information is flexible and easy to use without any constraints. The measurement items for construct perceived ease of use follow that of Khan et al. [40], and the developed five items include the following: (1) most of the e-government service information provided by government is easy to use; (2) I believe learning to use e-government from social media is easy; (3) I find social media as a flexible way of promoting strong relationships between citizens’ and e-government; (4) my interaction with government through social media about the use of e-government services would be clear and understandable; and (5) it would be easy for me to become skillful in using e-government services through social media. The items of perceived ease of use are measured with a 7-Likert scale ranging from 1=strongly disagree to 7=strongly agree.


### 4.1.3. Perceived Usefulness

Davis [49] and Chen and Aklikokou [42] defined perceived usefulness as to which citizens believe that using e-government information can improve effectiveness and performance and benefit the community. The study developed four measures based on Khan et al. [40] measurement items, including (1) using social media regarding government services can improve the service quality that I will receive about e-government; (2) using social media is increasing my effectiveness about e-government; (3) the use of social media can improve my performance to exchange information about e-government; and (4) generally, I find it useful to use information about e-government on social media. Perceived usefulness is measured on a 7-Likert scale ranging from 1=strongly disagree to 7=strongly agree.


### 4.1.4. Transparency

López-López et al. [61] and Sabani [2] defined transparency as to the availability of relevant information regarding government performance procedures and public policy decision-making processes that are implemented transparently to the public. Based on Hartanto et al. [62] measurement items, four measures were developed, including (1) the government plan and program about e-government are implemented transparently; (2) the entire process of plan and program about e-government is transparently disclosed; (3) the public can clearly see the progress and situations of the administration e-government; and (4) the government discloses sufficient information to the public about its performance implementing e-government. Transparency is measured on a 7-point Likert scale, where 1 indicates strongly disagree and 7 indicates strongly agree.


### 4.1.5. Accountability

According to Al-Shbail and Aman [58], accountability refers to the extent to which the government is responsible for its decisions and actions towards the community to achieve e-government program implementation performance. This study develops four items to measure accountability based on Hartanto et al. [62] including (1) the government has a regular reporting the achievements and results of the program against its objectives implementing e-government; (2) the government recognizes its responsibility toward the public through implementing e-government program; (3) the government abides by regulations in all circumstances in implementing e-government programs; and (4) the government ensures proper usage of its budget in an authorized performance in implementing e-government programs. We measure accountability on a 7-point Likert scale, where 1 indicates strongly disagree and 7 indicates strongly agree.


### 4.1.6. Responsiveness

According to Mansoor [18], responsiveness assures that the government cares about the suggestions, opinions, and demands of the community in improving the quality of e-government services. Based on Hartanto et al. [62], this study developed five responsiveness measures including (1) the government is sensitive to public opinions about e-government; (2) the government responds to public needs about e-government quickly; (3) the government is making sincere effort to support citizens who need help about e-government; (4) the government is efficient in providing quality solutions for public needs about e-government; and (5) citizen’s appeals to the government about e-government are treated properly within a reasonable period of time. Responsiveness is measured on a 7-Likert scale ranging from 1=strongly disagree to 7=strongly agree.


### 4.1.7. Trust to e-Government

According to Khan et al. [40], trust to e-government refers to the extent to which citizens understand the risk and uncertainty associated with using government so that they can rely on and trust e-government. According to Belanche et al. [63], this study develops three accountability measures including (1) I trust this e-government; (2) this e-government is reliable to carry out public services; and (3) when it comes to do public services, this e-government is trustworthy. Trust to e-government is measured on a 7-Likert scale ranging from 1=strongly disagree to 7=strongly agree.


### 4.1.8. e-Government Participation

According to Nam [6] and Khan et al. [40], e-government participation is the concept that describes citizens’ behavior formed after believing in e-government participation, where they interact and participate in decision-making processes related to public policies. This study develops five-item e-government participation according to Khan et al. [40] including (1) I intend to participate with e-government; (2) to participate with e-government is something that I would do; (3) I would use e-government information and services; (4) I predict I will participate with e-government in the future; and (5) I would not hesitate to engage with e-government. e-Government participation is measured on a 7-Likert scale ranging from 1=strongly disagree to 7=strongly agree.


## 4.1.1. Information Quality

Lee and Levy [47] and Khan et al. [40] defined information quality as public perception about e-government sources of information that are accurate, complete, relevant, up-to-date, and valuable according to the community’s needs. The measurement items for construct information quality follow that of Khan et al. [40], and the developed five items include the following: (1) I believe the government has provided accurate information of e-government through social media; (2) the government has provided an up-to-date information about e-government through social media; (3) I believe the government has provided the information meets to my needs about e-government through social media; (4) the government has provided relevant information about e-government through social media; and (5) the government has provided information about e-government which is easy to understand. The items of information quality are measured with a 7-Likert scale ranging from 1=strongly disagree to 7=strongly agree.


## 4.1.2. Perceived Ease of Use

According to Davis [49] and Khan et al. [40], perceived ease of use refers to the extent to which citizens believe that e-government information is flexible and easy to use without any constraints. The measurement items for construct perceived ease of use follow that of Khan et al. [40], and the developed five items include the following: (1) most of the e-government service information provided by government is easy to use; (2) I believe learning to use e-government from social media is easy; (3) I find social media as a flexible way of promoting strong relationships between citizens’ and e-government; (4) my interaction with government through social media about the use of e-government services would be clear and understandable; and (5) it would be easy for me to become skillful in using e-government services through social media. The items of perceived ease of use are measured with a 7-Likert scale ranging from 1=strongly disagree to 7=strongly agree.


## 4.1.3. Perceived Usefulness

Davis [49] and Chen and Aklikokou [42] defined perceived usefulness as to which citizens believe that using e-government information can improve effectiveness and performance and benefit the community. The study developed four measures based on Khan et al. [40] measurement items, including (1) using social media regarding government services can improve the service quality that I will receive about e-government; (2) using social media is increasing my effectiveness about e-government; (3) the use of social media can improve my performance to exchange information about e-government; and (4) generally, I find it useful to use information about e-government on social media. Perceived usefulness is measured on a 7-Likert scale ranging from 1=strongly disagree to 7=strongly agree.


## 4.1.4. Transparency

López-López et al. [61] and Sabani [2] defined transparency as to the availability of relevant information regarding government performance procedures and public policy decision-making processes that are implemented transparently to the public. Based on Hartanto et al. [62] measurement items, four measures were developed, including (1) the government plan and program about e-government are implemented transparently; (2) the entire process of plan and program about e-government is transparently disclosed; (3) the public can clearly see the progress and situations of the administration e-government; and (4) the government discloses sufficient information to the public about its performance implementing e-government. Transparency is measured on a 7-point Likert scale, where 1 indicates strongly disagree and 7 indicates strongly agree.


## 4.1.5. Accountability

According to Al-Shbail and Aman [58], accountability refers to the extent to which the government is responsible for its decisions and actions towards the community to achieve e-government program implementation performance. This study develops four items to measure accountability based on Hartanto et al. [62] including (1) the government has a regular reporting the achievements and results of the program against its objectives implementing e-government; (2) the government recognizes its responsibility toward the public through implementing e-government program; (3) the government abides by regulations in all circumstances in implementing e-government programs; and (4) the government ensures proper usage of its budget in an authorized performance in implementing e-government programs. We measure accountability on a 7-point Likert scale, where 1 indicates strongly disagree and 7 indicates strongly agree.


## 4.1.6. Responsiveness

According to Mansoor [18], responsiveness assures that the government cares about the suggestions, opinions, and demands of the community in improving the quality of e-government services. Based on Hartanto et al. [62], this study developed five responsiveness measures including (1) the government is sensitive to public opinions about e-government; (2) the government responds to public needs about e-government quickly; (3) the government is making sincere effort to support citizens who need help about e-government; (4) the government is efficient in providing quality solutions for public needs about e-government; and (5) citizen’s appeals to the government about e-government are treated properly within a reasonable period of time. Responsiveness is measured on a 7-Likert scale ranging from 1=strongly disagree to 7=strongly agree.


## 4.1.7. Trust to e-Government

According to Khan et al. [40], trust to e-government refers to the extent to which citizens understand the risk and uncertainty associated with using government so that they can rely on and trust e-government. According to Belanche et al. [63], this study develops three accountability measures including (1) I trust this e-government; (2) this e-government is reliable to carry out public services; and (3) when it comes to do public services, this e-government is trustworthy. Trust to e-government is measured on a 7-Likert scale ranging from 1=strongly disagree to 7=strongly agree.


## 4.1.8. e-Government Participation

According to Nam [6] and Khan et al. [40], e-government participation is the concept that describes citizens’ behavior formed after believing in e-government participation, where they interact and participate in decision-making processes related to public policies. This study develops five-item e-government participation according to Khan et al. [40] including (1) I intend to participate with e-government; (2) to participate with e-government is something that I would do; (3) I would use e-government information and services; (4) I predict I will participate with e-government in the future; and (5) I would not hesitate to engage with e-government. e-Government participation is measured on a 7-Likert scale ranging from 1=strongly disagree to 7=strongly agree.


## 4.2. Sampling Technique and Data Collection Procedure

In this study, research participants were selected using a purposive and a nonprobability sampling method. This survey targets a specific population and protects respondents’ privacy; therefore, we used an online survey to collect data. The research questionnaire includes two initial questions to ensure that respondents are aware of e-government information and implementation in Indonesia. Participants will be asked to confirm that they are familiar with government social media (e.g., Instagram, YouTube, and Facebook) and that they participate in discussions regarding the implementation of e-government in Indonesia through online media and the surrounding community. When a respondent answers “yes” to the two initial questions, he is qualified to produce consistent responses. This study collected respondent data using a Google Forms questionnaire distributed randomly through social media platforms (e.g., Instagram, WhatsApp, and Facebook). Previous studies also used the same data collection procedure [64, 65].


## 4.3. Analysis Techniques

In this study, two analysis approaches are used to test the data. First, structural equation modeling (SEM) will examine the causal relationship between variables. SEM analysis can be performed using SmartPLS 3.0 software. The measurement model is initially evaluated for convergent validity utilizing average variance extracted, composite reliability, and Cronbach’s alpha values for internal consistency [66]. Next, this study examined discriminant validity with the Fornell-Larcker criterion, heterotrait-monotrait (HTMT), and matrix cross-loading [67, 68]. To evaluate structural model strength explained by the endogenous constructs, this study follows Falk and Miller’s [69] R-square value (R2) to indicate the structural model’s strength.The second method of qualitative comparative analysis is fuzzy set qualitative comparative analysis (fsQCA), which tests propositions and determines whether the research model has asymmetrical relationships. A fsQCA test contributes to the development of theoretical and practical guidance by examining the theory’s complexity and its variables’ interdependence. A fsQCA analysis involves the following steps. The first step in the fsQCA test is calibration selection, which transforms 7-Likert scales into fuzzy data sets, such as “2” for nonmembership, “6” for membership, and “4” for the intersection [70]. A truth table is used to arrange the scores obtained and analyze them in light of the causal conditions of the independent variables. Based on the findings of this analysis, fsQCA was conducted to identify the most efficient and unique solution [70].


## 5. Result

### 5.1. Demographic Profile

There were 455 responses collected. Based on gender, 53.6% of respondents were women, followed by most respondents aged 21 to 30 years old. A number of the respondents are graduates with a work status as a student of 37.8%. 97.1% of people are familiar with government social media (e.g., Instagram, YouTube, and Facebook) as a source of e-government information. Additionally, 88.6% of respondents participated in discussions on e-government implementation, both through online media and in person. A summary of the demographic characteristics of the respondents is presented in Table2.Table 2
Respondent demographics.
MeasureItemsFrequencyPercentageGenderMale21146.4%Female24453.6%Age (years old)20 or below7115.6%21 to 3019142%31 to 4010322.6%41 to 506313.8%51 or above275.9%Educational backgroundSenior high school10723.5%Vocational school5512.1%Undergraduate19142%Master7215.8%Doctorate306.6%OccupationUniversity student17237.8%Entrepreneurs5612.3%Civil servant12026.4%Private employee6514.3%State-owned enterprises429.2%


### 5.2. Results from SEM Analysis

#### 5.2.1. Common Method Variance

This study used the self-reported questionnaire method to collect data from respondents, so evaluating the common method variance (CMV) is imperative. Harman’s single-factor method was applied to evaluate the common method variance. Performing this test requires all constructs to be inserted simultaneously. Assuming that all constructs are loaded on one factor, which accounts for all or most variance, there will be a high level of common method variance [71]. It was found that the explained variance is 29.3% which is below 50%. This implies that there is concern about common method variance.


#### 5.2.2. Validity and Reliability Assessment

Table3 summarizes convergent validity and internal consistency results. Based on data analysis, each construct’s outer loading value exceeds 0.70 [66], which indicates that construct validity is satisfactory. On the other hand, the value of average variable extracted (AVE) is higher than 0.5 and satisfactory for convergent validity, according to Hair et al. [66]. The internal consistency is measured with Cronbach’s alpha (CA) value higher than 0.70, which is satisfactory. Further, each construct’s composite reliability (CR) value is above 0.70, which is satisfactory [66]. Therefore, this study has no issues with convergent validity and internal consistency.Table 3
Convergent validity and internal consistency.
ConstructItemsLoadingsCACRAVEInformation quality (IQ)IQ10.7760.8020.8110.627IQ20.814IQ40.750IQ50.826Perceived ease of use (PEOU)PEOU10.7640.7680.7820.589PEOU20.782PEOU40.700PEOU50.826Perceived usefulness (PU)PU10.8030.7940.7980.617PU20.793PU30.770PU40.775Responsiveness (RV)RV10.8090.8030.8090.629RV20.835RV40.728RV50.797Accountability (AT)AT10.7940.8100.8200.635AT20.821AT30.790AT40.783Transparency (TP)TP10.7640.7970.8070.622TP20.844TP30.811TP40.732Trust to e-government (TTE)TTE10.8330.8120.8140.727TTE20.898TTE30.826e-Government participation (EP)EP10.7690.8400.8420.610EP20.793EP30.760EP40.797EP50.784Notes:loading≥0.7; CA: Cronbach’salpha≥0.7; CR: composite reliability≥0.7; AVE: average variance extracted≥0.5.There are three approaches to assessing discriminant validity. The first is the Fornell-Larcker criterion, which is calculated by taking the square root of the AVE divided by the interconstruct correlation. The results in Table4 demonstrate that the square roots of AVE are higher than the correlation between constructs (below the diagonal values in italic). This indicates satisfactory discriminant validity with the Fornell-Larcker criterion [67].Table 4
Discriminant validity with the Fornell-Larcker criterion.
ConstructIQPEOUPURVATTPTTEEPInformation quality (IQ)0.792Perceived ease of use (PEOU)0.6910.768Perceived usefulness (PU)0.6070.7320.785Responsiveness (RV)0.5590.5940.5560.793Accountability (AT)0.5550.5750.5740.740.797Transparency (TP)0.5600.5900.5360.6840.7320.789Trust to e-government (TTE)0.5170.6200.6610.5300.5540.5550.853e-Government participation (EP)0.5470.6570.7260.4950.5190.5130.7080.781Notes: the diagonal and italic values are the square roots of AVE.Second, as a new criterion, the heterotrait-monotrait ratio (HTMT) assesses discriminant validity with a strict threshold of 0.95 [68]. The analysis in Table 5 indicates that the HTMT value is below 0.95, which is satisfactory for discriminant validity with HTMT criteria [68].Table 5
Heterotrait-monotrait ratio (HTMT).
ConstructIQPEOUPURVATTPTTEEPInformation quality (IQ)—Perceived ease of use (PEOU)0.881—Perceived usefulness (PU)0.7620.828—Responsiveness (RV)0.6950.7620.690—Accountability (AT)0.6870.7330.7120.822—Transparency (TP)0.7000.7570.6700.8560.809—Trust to e-government (TTE)0.6380.7770.8170.6500.6710.686—e-Government participation (EP)0.6640.8150.8850.5980.6220.6240.855—Notes: threshold of HTMT, ≤0.85, strong; ≤0.90, weak.Third is the cross-loading matrix approach. In Table6, all constructs have outer loadings greater than their correlation coefficients. Therefore, each construct is discriminantly valid, which leads to a good assessment of the measurement model and a move toward formulating a model hypothesis.Table 6
Cross loading matrix.
ConstructIQPEOUPURVATTPTTEEPIQ10.7760.4650.3920.4100.4220.4470.3780.339IQ20.8140.5340.4680.4380.4390.4580.4480.443IQ40.7500.5870.5430.4350.4210.3900.3530.477IQ50.8260.6060.5240.4870.4750.4720.4490.472PEOU10.5550.7640.5150.5090.4730.4540.4570.478PEOU20.5660.7820.5940.4260.4330.4620.5110.509PEOU40.4680.6920.5080.4690.4370.4490.3720.455PEOU50.5320.8260.6210.4410.4370.4550.5420.566PU10.5150.6230.8030.4770.4440.4060.5290.580PU20.4660.6220.7930.4750.4680.4880.5840.604PU30.4370.5050.7700.4030.4490.3860.4830.544PU40.4890.5370.7750.3780.4430.3920.4660.545RV10.4530.4600.4140.8090.5820.5300.4220.406RV20.4470.5050.4320.8350.5790.5790.4720.393RV40.4530.4840.5110.7280.5650.5100.4120.423RV50.4200.4270.4040.7970.6330.5510.3600.342AT10.4480.4380.4220.6340.7940.5730.3810.367AT20.4630.4890.4770.6170.8210.6140.5180.439AT30.4260.4480.4470.5600.7900.5560.3830.370AT40.4300.4520.4780.5510.7830.5830.4550.463TP10.4330.4260.4500.5580.6290.7640.4140.446TP20.4430.5140.4330.5600.5950.8440.4980.438TP30.4710.4860.4120.5530.5700.8110.4430.386TP40.4220.4300.3980.4890.5170.7320.3860.344TTE10.4570.5100.5460.5120.5010.4970.8330.589TTE20.4200.5460.6020.4690.4950.5020.8980.621TTE30.4480.5310.5400.3730.4190.4180.8260.600EP10.4540.4820.5630.4190.4160.3950.5940.769EP20.4530.5460.5690.4100.4170.4500.5710.793EP30.3890.5140.5420.3530.3820.3690.5060.760EP40.4170.5040.5920.3640.3990.4080.5590.797EP50.4130.5200.5670.3800.4100.3730.5250.784Notes: the italicized values indicated construct loadings.


#### 5.2.3. Hypothesis Results

As a part of this study, SmartPLS 3.0 software is utilized to perform structural equation modeling with partial least squares (PLS-SEM) to evaluate the validity of the research model used to test hypotheses. First, in order to determine the power of an endogenous variable model, this study determines the path coefficient between the model’s constructs. TheR2 value of a valid approach should be greater than or close to 0.1 [68]. According to the analysis, trust in e-government has an R2=0.515, which is explained by the path coefficients of perceived ease of use, perceived usefulness, transparency, accountability, and responsiveness. The trust to e-government path coefficient can be explained by the e-government participation construct with an R2 value of 0.501. As a result, this research model was determined to be viable with an endogenous construct having an R2 value greater than 0.1 [69].As shown in Figure3 and Table 7, trust in e-government is a predictor that can promote participation in e-government, thereby supporting H1 (β=0.708 and t=24.154). From the social media perspective, it was found that there was no significant effect of information quality on trust in e-government, with H2a not being supported (β=0.015 and t=0.258). Conversely, perceived ease of use and perceived usefulness significantly affect trust in e-government; thus, confirming H2b and H2c (β=0.175 and 0.367 and t=2.629 and 5.480, respectively). In contrast, from the perspective of good governance, transparency relates positively to trust toward e-government, supporting H3a (β=0.149 and t=2.175). Lastly, accountability and responsiveness have no significant effect on trust in e-government; therefore, both H3b and H3c are not supported (β=0.093 and 0.042 and t=1.186 and 0.636, respectively).Figure 3
Structural model results.Table 7
Summary of hypothesis testing.
HypothesisPath coefficientsT valueConclusionH1. Trust to e-government ➔ e-government participation0.708∗∗∗24,154SupportedH2a. Information quality ➔ trust to e-government0.0150.258UnsupportedH2b. Perceived ease of use ➔ trust to e-government0.175∗∗2,629SupportedH2c. Perceived usefulness ➔ trust to e-government0.367∗∗∗5,480SupportedH3a. Transparency ➔ trust to e-government0.149∗2,175SupportedH3b. Accountability ➔ trust to e-government0.0931,186UnsupportedH3c. Responsiveness ➔ trust to e-government0.0420.636UnsupportedNotes:∗∗∗P<0.001, ∗∗P<0.01, and ∗P<0.05. ns: nonsignificant.


### 5.3. Results from fsQCA

#### 5.3.1. Calibration Selection and Truth Table Construction

This study uses fsQCA analysis to produce high and low e-government participation configurations as outcome variables moulded from the constructs of trust in e-government, social media (information quality, perceived ease of use, and perceived usefulness), and good governance (transparency, responsiveness, and accountability). This study will use the analysis results to resolve a complex issue developing from interdimensional relationships between constructs in the research model. First, in order to transform the data, Pappas and Woodside [70] advocate calibrating the seven-Likert scale into three groups (“6” indicates a full membership, “4” indicates the intersection or median, and “2” indicates a full nonmembership). Therefore, the calibrated data then converts to fuzzy scores of “0”, “low,” and “1”, “high,” and arranged in a truth table that represents entire possible composite conditions that reproduce “high” and “low” participation in e-government. The calibration results are presented in Tables 8 and 9.Table 8
Truth table for high e-government participation.
Antecedents for high e-government participationIQPEOUPURVATTPTTECasesOutcome for high e-government participationRaw consistency11101113Yes0.99711111016Yes0.99611100114Yes0.99501111119Yes0.99211110114Yes0.99011111103Yes0.98811110016Yes0.9871111111319Yes0.985Notes: IQ: information quality; PEOU: perceived ease of use; PU: perceived usefulness; RV: responsiveness; AT: accountability; TP: transparency; TTE: trust to e-government; EP: e-government participation.Table 9
Truth table for low e-government participation.
Antecedents for low e-government participationIQPEOUPURVATTPTTECasesOutcome for low e-government participationRaw consistency11111103No0.77311110016No0.73411100114No0.73611110114No0.70501111119No0.68711101113No0.66511111016No0.6651111111319No0.203Notes: IQ: information quality; PEOU: perceived ease of use; PU: perceived usefulness; RV: responsiveness; AT: accountability; TP: transparency; TTE: trust to e-government; EP: e-government participation.According to a truth table analysis, eight composite indicators with scores of “1” (yes) indicate a high level of participation in e-government. In particular, there were nine cases in the fifth composite and 319 cases in the eighth composite, while the remaining cases were less than six. However, eight cases are considered to have a low level of participation in e-government, with a score of “0” (no). There were nine cases in the second and third composite conditions, along with 319 cases in the eighth composite condition, and less than six cases represented low levels of participation in e-government. Therefore, this study indicates that the fuzzy set for analyzing high and low levels of participation in e-government is diverse and unique.


#### 5.3.2. fsQCA Findings

The results of the fsQCA analysis of intermediate solutions, including core and peripheral conditions, form high and low e-government participation, are presented in Table10. It is evident from the solutions that two configurations exist that describe “high” and “low” levels of e-government participation. Ragin [72] recommended that the consistency value for “high” levels of overall results is more significant than 0.75, which indicates a combination of causal conditions that are highly relevant and acceptable. For high e-government participation outcomes, the overall solution consistency value is 0.973, and the overall solution coverage value is 0.878, and for “low” e-government participation outcomes, the overall consistency value is 0.769, and the overall solution coverage value is 0.879. This score reflects a better prediction for both results of “high” and “low” participation in e-government activities.Table 10
Configuration for “high” and “low” e-government participation.
ConfigurationHigh e-government participationLow e-government participationP1P2P3P4Trust to e-government (TTE)●●Social mediaInformation quality (IQ)●●Perceived ease of use (PEOU)●●⨂Perceived usefulness (PU)●●⨂Good governanceTransparency (TR)●Accountability (AT)Responsiveness (RV)●Raw coverage0.8240.8200.7950.800Unique coverage0.0300.0260.0150.017Consistency0.9800.9810.9820.982Overall solution coverage0.8780.879Overall solution consistency0.9730.769Note: black circle (●) indicates the presence of condition; a circle with a cross (⨂) indicates the absence of condition; blank column shows “do not care” condition.Figures4 and 5 present the results of the fsQCA configuration with high consistency and relevance to form high participation in e-government. The entire configurations lead to “presence” (∗) conditions and are unique, thus supporting Proposition 1. Further, the first path (P1) for outcome high e-government participation is moulded by combining the “presence” conditions of ∗TTE, ∗IQ, ∗PEOU, ∗PU, ∗RV, and “do not care” conditions of TP and AT (consistency=0.980 and coverage=0.824). The results from path 1 illustrate how trust in e-government is an essential predictor of increasing e-government participation in e-government use. As a result, trust is formed by social media, which contains high-quality e-government information, perceived ease of use, perceived usefulness, and good governance, namely, the responsiveness of the government to the public. The second configuration (P2), which incorporates “presence” conditions of ∗TTE, ∗IQ, ∗PEOU, ∗PU, ∗TP, and “do not care” condition for AT and RV, also results in a high level of e-government participation (consistency=0.981 and coverage=0.820).Figure 4
Path 1 contributes to high e-government participation (HEP) (consistency=0.980 and coverage=0.824). Note: the solid ellipse represents the presence of the condition. If no ellipse is displayed, it belongs to the “do not care” condition.Figure 5
Path 2 contributes to high e-government participation (HEP) (consistency=0.981 and coverage=0.820). Note: the solid ellipse represents the presence of the condition. If no ellipse is displayed, it belongs to the “do not care” condition.As shown in Figures6 and 7, the results of the fsQCA configuration with a high level of consistency and relevance for a “low” level of e-government participation are visualized. The results demonstrate that overall solution coverage is 0.879 and solution consistency is 0.769, which follows Ragin’s [72] recommendations. Results of the study demonstrate that a configurational path with “low” e-government participation can be derived from a combination of trust, social media, and good governance, thus supporting Proposition 2. In more detail, the configuration (P3 and P4) produces a combination of “absence” and “do not care” conditions. The configurational path 3 (P3) shows an “absence” (~) condition of perceived ease of use (~PEOU) and “do not care” conditions of TTE, IQ, PU, TR, AT, and RV with a higher relevance value than the other configurations (consistency=0.982 and coverage=0.810). This indicates that the information of e-government on social media still needs to be flexible to use and cannot satisfy the public’s electronic and informational needs. This ultimately results in a low level of participation in e-government. Furthermore, the fourth configuration (P4) demonstrates an absence of perceived usefulness (~PU) and “do not care” conditions of TTE, IQ, PEOU, TR, A, and RV condition with a high relevance value (consistency=0.982 and coverage=0.795). This configuration shows that the benefits of PU in e-government information on social media cannot be perceived as valuable by citizens, which results in a low participation rate.Figure 6
Path 3 contributes to low e-government participation (LEP) (consistency=0.982 and coverage=0.795). Note: the dotted ellipse represents the absence of the condition. If no ellipse displayed, it belongs to the “do not care” condition.Figure 7
Path 4 contributes to low e-government participation (LEP) (consistency=0.982 and coverage=0.800). Note: the dotted ellipse represents the absence of the condition. If no ellipse displayed, it belongs to the “do not care” condition.


## 5.1. Demographic Profile

There were 455 responses collected. Based on gender, 53.6% of respondents were women, followed by most respondents aged 21 to 30 years old. A number of the respondents are graduates with a work status as a student of 37.8%. 97.1% of people are familiar with government social media (e.g., Instagram, YouTube, and Facebook) as a source of e-government information. Additionally, 88.6% of respondents participated in discussions on e-government implementation, both through online media and in person. A summary of the demographic characteristics of the respondents is presented in Table2.Table 2
Respondent demographics.
MeasureItemsFrequencyPercentageGenderMale21146.4%Female24453.6%Age (years old)20 or below7115.6%21 to 3019142%31 to 4010322.6%41 to 506313.8%51 or above275.9%Educational backgroundSenior high school10723.5%Vocational school5512.1%Undergraduate19142%Master7215.8%Doctorate306.6%OccupationUniversity student17237.8%Entrepreneurs5612.3%Civil servant12026.4%Private employee6514.3%State-owned enterprises429.2%


## 5.2. Results from SEM Analysis

### 5.2.1. Common Method Variance

This study used the self-reported questionnaire method to collect data from respondents, so evaluating the common method variance (CMV) is imperative. Harman’s single-factor method was applied to evaluate the common method variance. Performing this test requires all constructs to be inserted simultaneously. Assuming that all constructs are loaded on one factor, which accounts for all or most variance, there will be a high level of common method variance [71]. It was found that the explained variance is 29.3% which is below 50%. This implies that there is concern about common method variance.


### 5.2.2. Validity and Reliability Assessment

Table3 summarizes convergent validity and internal consistency results. Based on data analysis, each construct’s outer loading value exceeds 0.70 [66], which indicates that construct validity is satisfactory. On the other hand, the value of average variable extracted (AVE) is higher than 0.5 and satisfactory for convergent validity, according to Hair et al. [66]. The internal consistency is measured with Cronbach’s alpha (CA) value higher than 0.70, which is satisfactory. Further, each construct’s composite reliability (CR) value is above 0.70, which is satisfactory [66]. Therefore, this study has no issues with convergent validity and internal consistency.Table 3
Convergent validity and internal consistency.
ConstructItemsLoadingsCACRAVEInformation quality (IQ)IQ10.7760.8020.8110.627IQ20.814IQ40.750IQ50.826Perceived ease of use (PEOU)PEOU10.7640.7680.7820.589PEOU20.782PEOU40.700PEOU50.826Perceived usefulness (PU)PU10.8030.7940.7980.617PU20.793PU30.770PU40.775Responsiveness (RV)RV10.8090.8030.8090.629RV20.835RV40.728RV50.797Accountability (AT)AT10.7940.8100.8200.635AT20.821AT30.790AT40.783Transparency (TP)TP10.7640.7970.8070.622TP20.844TP30.811TP40.732Trust to e-government (TTE)TTE10.8330.8120.8140.727TTE20.898TTE30.826e-Government participation (EP)EP10.7690.8400.8420.610EP20.793EP30.760EP40.797EP50.784Notes:loading≥0.7; CA: Cronbach’salpha≥0.7; CR: composite reliability≥0.7; AVE: average variance extracted≥0.5.There are three approaches to assessing discriminant validity. The first is the Fornell-Larcker criterion, which is calculated by taking the square root of the AVE divided by the interconstruct correlation. The results in Table4 demonstrate that the square roots of AVE are higher than the correlation between constructs (below the diagonal values in italic). This indicates satisfactory discriminant validity with the Fornell-Larcker criterion [67].Table 4
Discriminant validity with the Fornell-Larcker criterion.
ConstructIQPEOUPURVATTPTTEEPInformation quality (IQ)0.792Perceived ease of use (PEOU)0.6910.768Perceived usefulness (PU)0.6070.7320.785Responsiveness (RV)0.5590.5940.5560.793Accountability (AT)0.5550.5750.5740.740.797Transparency (TP)0.5600.5900.5360.6840.7320.789Trust to e-government (TTE)0.5170.6200.6610.5300.5540.5550.853e-Government participation (EP)0.5470.6570.7260.4950.5190.5130.7080.781Notes: the diagonal and italic values are the square roots of AVE.Second, as a new criterion, the heterotrait-monotrait ratio (HTMT) assesses discriminant validity with a strict threshold of 0.95 [68]. The analysis in Table 5 indicates that the HTMT value is below 0.95, which is satisfactory for discriminant validity with HTMT criteria [68].Table 5
Heterotrait-monotrait ratio (HTMT).
ConstructIQPEOUPURVATTPTTEEPInformation quality (IQ)—Perceived ease of use (PEOU)0.881—Perceived usefulness (PU)0.7620.828—Responsiveness (RV)0.6950.7620.690—Accountability (AT)0.6870.7330.7120.822—Transparency (TP)0.7000.7570.6700.8560.809—Trust to e-government (TTE)0.6380.7770.8170.6500.6710.686—e-Government participation (EP)0.6640.8150.8850.5980.6220.6240.855—Notes: threshold of HTMT, ≤0.85, strong; ≤0.90, weak.Third is the cross-loading matrix approach. In Table6, all constructs have outer loadings greater than their correlation coefficients. Therefore, each construct is discriminantly valid, which leads to a good assessment of the measurement model and a move toward formulating a model hypothesis.Table 6
Cross loading matrix.
ConstructIQPEOUPURVATTPTTEEPIQ10.7760.4650.3920.4100.4220.4470.3780.339IQ20.8140.5340.4680.4380.4390.4580.4480.443IQ40.7500.5870.5430.4350.4210.3900.3530.477IQ50.8260.6060.5240.4870.4750.4720.4490.472PEOU10.5550.7640.5150.5090.4730.4540.4570.478PEOU20.5660.7820.5940.4260.4330.4620.5110.509PEOU40.4680.6920.5080.4690.4370.4490.3720.455PEOU50.5320.8260.6210.4410.4370.4550.5420.566PU10.5150.6230.8030.4770.4440.4060.5290.580PU20.4660.6220.7930.4750.4680.4880.5840.604PU30.4370.5050.7700.4030.4490.3860.4830.544PU40.4890.5370.7750.3780.4430.3920.4660.545RV10.4530.4600.4140.8090.5820.5300.4220.406RV20.4470.5050.4320.8350.5790.5790.4720.393RV40.4530.4840.5110.7280.5650.5100.4120.423RV50.4200.4270.4040.7970.6330.5510.3600.342AT10.4480.4380.4220.6340.7940.5730.3810.367AT20.4630.4890.4770.6170.8210.6140.5180.439AT30.4260.4480.4470.5600.7900.5560.3830.370AT40.4300.4520.4780.5510.7830.5830.4550.463TP10.4330.4260.4500.5580.6290.7640.4140.446TP20.4430.5140.4330.5600.5950.8440.4980.438TP30.4710.4860.4120.5530.5700.8110.4430.386TP40.4220.4300.3980.4890.5170.7320.3860.344TTE10.4570.5100.5460.5120.5010.4970.8330.589TTE20.4200.5460.6020.4690.4950.5020.8980.621TTE30.4480.5310.5400.3730.4190.4180.8260.600EP10.4540.4820.5630.4190.4160.3950.5940.769EP20.4530.5460.5690.4100.4170.4500.5710.793EP30.3890.5140.5420.3530.3820.3690.5060.760EP40.4170.5040.5920.3640.3990.4080.5590.797EP50.4130.5200.5670.3800.4100.3730.5250.784Notes: the italicized values indicated construct loadings.


### 5.2.3. Hypothesis Results

As a part of this study, SmartPLS 3.0 software is utilized to perform structural equation modeling with partial least squares (PLS-SEM) to evaluate the validity of the research model used to test hypotheses. First, in order to determine the power of an endogenous variable model, this study determines the path coefficient between the model’s constructs. TheR2 value of a valid approach should be greater than or close to 0.1 [68]. According to the analysis, trust in e-government has an R2=0.515, which is explained by the path coefficients of perceived ease of use, perceived usefulness, transparency, accountability, and responsiveness. The trust to e-government path coefficient can be explained by the e-government participation construct with an R2 value of 0.501. As a result, this research model was determined to be viable with an endogenous construct having an R2 value greater than 0.1 [69].As shown in Figure3 and Table 7, trust in e-government is a predictor that can promote participation in e-government, thereby supporting H1 (β=0.708 and t=24.154). From the social media perspective, it was found that there was no significant effect of information quality on trust in e-government, with H2a not being supported (β=0.015 and t=0.258). Conversely, perceived ease of use and perceived usefulness significantly affect trust in e-government; thus, confirming H2b and H2c (β=0.175 and 0.367 and t=2.629 and 5.480, respectively). In contrast, from the perspective of good governance, transparency relates positively to trust toward e-government, supporting H3a (β=0.149 and t=2.175). Lastly, accountability and responsiveness have no significant effect on trust in e-government; therefore, both H3b and H3c are not supported (β=0.093 and 0.042 and t=1.186 and 0.636, respectively).Figure 3
Structural model results.Table 7
Summary of hypothesis testing.
HypothesisPath coefficientsT valueConclusionH1. Trust to e-government ➔ e-government participation0.708∗∗∗24,154SupportedH2a. Information quality ➔ trust to e-government0.0150.258UnsupportedH2b. Perceived ease of use ➔ trust to e-government0.175∗∗2,629SupportedH2c. Perceived usefulness ➔ trust to e-government0.367∗∗∗5,480SupportedH3a. Transparency ➔ trust to e-government0.149∗2,175SupportedH3b. Accountability ➔ trust to e-government0.0931,186UnsupportedH3c. Responsiveness ➔ trust to e-government0.0420.636UnsupportedNotes:∗∗∗P<0.001, ∗∗P<0.01, and ∗P<0.05. ns: nonsignificant.


## 5.2.1. Common Method Variance

This study used the self-reported questionnaire method to collect data from respondents, so evaluating the common method variance (CMV) is imperative. Harman’s single-factor method was applied to evaluate the common method variance. Performing this test requires all constructs to be inserted simultaneously. Assuming that all constructs are loaded on one factor, which accounts for all or most variance, there will be a high level of common method variance [71]. It was found that the explained variance is 29.3% which is below 50%. This implies that there is concern about common method variance.


## 5.2.2. Validity and Reliability Assessment

Table3 summarizes convergent validity and internal consistency results. Based on data analysis, each construct’s outer loading value exceeds 0.70 [66], which indicates that construct validity is satisfactory. On the other hand, the value of average variable extracted (AVE) is higher than 0.5 and satisfactory for convergent validity, according to Hair et al. [66]. The internal consistency is measured with Cronbach’s alpha (CA) value higher than 0.70, which is satisfactory. Further, each construct’s composite reliability (CR) value is above 0.70, which is satisfactory [66]. Therefore, this study has no issues with convergent validity and internal consistency.Table 3
Convergent validity and internal consistency.
ConstructItemsLoadingsCACRAVEInformation quality (IQ)IQ10.7760.8020.8110.627IQ20.814IQ40.750IQ50.826Perceived ease of use (PEOU)PEOU10.7640.7680.7820.589PEOU20.782PEOU40.700PEOU50.826Perceived usefulness (PU)PU10.8030.7940.7980.617PU20.793PU30.770PU40.775Responsiveness (RV)RV10.8090.8030.8090.629RV20.835RV40.728RV50.797Accountability (AT)AT10.7940.8100.8200.635AT20.821AT30.790AT40.783Transparency (TP)TP10.7640.7970.8070.622TP20.844TP30.811TP40.732Trust to e-government (TTE)TTE10.8330.8120.8140.727TTE20.898TTE30.826e-Government participation (EP)EP10.7690.8400.8420.610EP20.793EP30.760EP40.797EP50.784Notes:loading≥0.7; CA: Cronbach’salpha≥0.7; CR: composite reliability≥0.7; AVE: average variance extracted≥0.5.There are three approaches to assessing discriminant validity. The first is the Fornell-Larcker criterion, which is calculated by taking the square root of the AVE divided by the interconstruct correlation. The results in Table4 demonstrate that the square roots of AVE are higher than the correlation between constructs (below the diagonal values in italic). This indicates satisfactory discriminant validity with the Fornell-Larcker criterion [67].Table 4
Discriminant validity with the Fornell-Larcker criterion.
ConstructIQPEOUPURVATTPTTEEPInformation quality (IQ)0.792Perceived ease of use (PEOU)0.6910.768Perceived usefulness (PU)0.6070.7320.785Responsiveness (RV)0.5590.5940.5560.793Accountability (AT)0.5550.5750.5740.740.797Transparency (TP)0.5600.5900.5360.6840.7320.789Trust to e-government (TTE)0.5170.6200.6610.5300.5540.5550.853e-Government participation (EP)0.5470.6570.7260.4950.5190.5130.7080.781Notes: the diagonal and italic values are the square roots of AVE.Second, as a new criterion, the heterotrait-monotrait ratio (HTMT) assesses discriminant validity with a strict threshold of 0.95 [68]. The analysis in Table 5 indicates that the HTMT value is below 0.95, which is satisfactory for discriminant validity with HTMT criteria [68].Table 5
Heterotrait-monotrait ratio (HTMT).
ConstructIQPEOUPURVATTPTTEEPInformation quality (IQ)—Perceived ease of use (PEOU)0.881—Perceived usefulness (PU)0.7620.828—Responsiveness (RV)0.6950.7620.690—Accountability (AT)0.6870.7330.7120.822—Transparency (TP)0.7000.7570.6700.8560.809—Trust to e-government (TTE)0.6380.7770.8170.6500.6710.686—e-Government participation (EP)0.6640.8150.8850.5980.6220.6240.855—Notes: threshold of HTMT, ≤0.85, strong; ≤0.90, weak.Third is the cross-loading matrix approach. In Table6, all constructs have outer loadings greater than their correlation coefficients. Therefore, each construct is discriminantly valid, which leads to a good assessment of the measurement model and a move toward formulating a model hypothesis.Table 6
Cross loading matrix.
ConstructIQPEOUPURVATTPTTEEPIQ10.7760.4650.3920.4100.4220.4470.3780.339IQ20.8140.5340.4680.4380.4390.4580.4480.443IQ40.7500.5870.5430.4350.4210.3900.3530.477IQ50.8260.6060.5240.4870.4750.4720.4490.472PEOU10.5550.7640.5150.5090.4730.4540.4570.478PEOU20.5660.7820.5940.4260.4330.4620.5110.509PEOU40.4680.6920.5080.4690.4370.4490.3720.455PEOU50.5320.8260.6210.4410.4370.4550.5420.566PU10.5150.6230.8030.4770.4440.4060.5290.580PU20.4660.6220.7930.4750.4680.4880.5840.604PU30.4370.5050.7700.4030.4490.3860.4830.544PU40.4890.5370.7750.3780.4430.3920.4660.545RV10.4530.4600.4140.8090.5820.5300.4220.406RV20.4470.5050.4320.8350.5790.5790.4720.393RV40.4530.4840.5110.7280.5650.5100.4120.423RV50.4200.4270.4040.7970.6330.5510.3600.342AT10.4480.4380.4220.6340.7940.5730.3810.367AT20.4630.4890.4770.6170.8210.6140.5180.439AT30.4260.4480.4470.5600.7900.5560.3830.370AT40.4300.4520.4780.5510.7830.5830.4550.463TP10.4330.4260.4500.5580.6290.7640.4140.446TP20.4430.5140.4330.5600.5950.8440.4980.438TP30.4710.4860.4120.5530.5700.8110.4430.386TP40.4220.4300.3980.4890.5170.7320.3860.344TTE10.4570.5100.5460.5120.5010.4970.8330.589TTE20.4200.5460.6020.4690.4950.5020.8980.621TTE30.4480.5310.5400.3730.4190.4180.8260.600EP10.4540.4820.5630.4190.4160.3950.5940.769EP20.4530.5460.5690.4100.4170.4500.5710.793EP30.3890.5140.5420.3530.3820.3690.5060.760EP40.4170.5040.5920.3640.3990.4080.5590.797EP50.4130.5200.5670.3800.4100.3730.5250.784Notes: the italicized values indicated construct loadings.


## 5.2.3. Hypothesis Results

As a part of this study, SmartPLS 3.0 software is utilized to perform structural equation modeling with partial least squares (PLS-SEM) to evaluate the validity of the research model used to test hypotheses. First, in order to determine the power of an endogenous variable model, this study determines the path coefficient between the model’s constructs. TheR2 value of a valid approach should be greater than or close to 0.1 [68]. According to the analysis, trust in e-government has an R2=0.515, which is explained by the path coefficients of perceived ease of use, perceived usefulness, transparency, accountability, and responsiveness. The trust to e-government path coefficient can be explained by the e-government participation construct with an R2 value of 0.501. As a result, this research model was determined to be viable with an endogenous construct having an R2 value greater than 0.1 [69].As shown in Figure3 and Table 7, trust in e-government is a predictor that can promote participation in e-government, thereby supporting H1 (β=0.708 and t=24.154). From the social media perspective, it was found that there was no significant effect of information quality on trust in e-government, with H2a not being supported (β=0.015 and t=0.258). Conversely, perceived ease of use and perceived usefulness significantly affect trust in e-government; thus, confirming H2b and H2c (β=0.175 and 0.367 and t=2.629 and 5.480, respectively). In contrast, from the perspective of good governance, transparency relates positively to trust toward e-government, supporting H3a (β=0.149 and t=2.175). Lastly, accountability and responsiveness have no significant effect on trust in e-government; therefore, both H3b and H3c are not supported (β=0.093 and 0.042 and t=1.186 and 0.636, respectively).Figure 3
Structural model results.Table 7
Summary of hypothesis testing.
HypothesisPath coefficientsT valueConclusionH1. Trust to e-government ➔ e-government participation0.708∗∗∗24,154SupportedH2a. Information quality ➔ trust to e-government0.0150.258UnsupportedH2b. Perceived ease of use ➔ trust to e-government0.175∗∗2,629SupportedH2c. Perceived usefulness ➔ trust to e-government0.367∗∗∗5,480SupportedH3a. Transparency ➔ trust to e-government0.149∗2,175SupportedH3b. Accountability ➔ trust to e-government0.0931,186UnsupportedH3c. Responsiveness ➔ trust to e-government0.0420.636UnsupportedNotes:∗∗∗P<0.001, ∗∗P<0.01, and ∗P<0.05. ns: nonsignificant.


## 5.3. Results from fsQCA

### 5.3.1. Calibration Selection and Truth Table Construction

This study uses fsQCA analysis to produce high and low e-government participation configurations as outcome variables moulded from the constructs of trust in e-government, social media (information quality, perceived ease of use, and perceived usefulness), and good governance (transparency, responsiveness, and accountability). This study will use the analysis results to resolve a complex issue developing from interdimensional relationships between constructs in the research model. First, in order to transform the data, Pappas and Woodside [70] advocate calibrating the seven-Likert scale into three groups (“6” indicates a full membership, “4” indicates the intersection or median, and “2” indicates a full nonmembership). Therefore, the calibrated data then converts to fuzzy scores of “0”, “low,” and “1”, “high,” and arranged in a truth table that represents entire possible composite conditions that reproduce “high” and “low” participation in e-government. The calibration results are presented in Tables 8 and 9.Table 8
Truth table for high e-government participation.
Antecedents for high e-government participationIQPEOUPURVATTPTTECasesOutcome for high e-government participationRaw consistency11101113Yes0.99711111016Yes0.99611100114Yes0.99501111119Yes0.99211110114Yes0.99011111103Yes0.98811110016Yes0.9871111111319Yes0.985Notes: IQ: information quality; PEOU: perceived ease of use; PU: perceived usefulness; RV: responsiveness; AT: accountability; TP: transparency; TTE: trust to e-government; EP: e-government participation.Table 9
Truth table for low e-government participation.
Antecedents for low e-government participationIQPEOUPURVATTPTTECasesOutcome for low e-government participationRaw consistency11111103No0.77311110016No0.73411100114No0.73611110114No0.70501111119No0.68711101113No0.66511111016No0.6651111111319No0.203Notes: IQ: information quality; PEOU: perceived ease of use; PU: perceived usefulness; RV: responsiveness; AT: accountability; TP: transparency; TTE: trust to e-government; EP: e-government participation.According to a truth table analysis, eight composite indicators with scores of “1” (yes) indicate a high level of participation in e-government. In particular, there were nine cases in the fifth composite and 319 cases in the eighth composite, while the remaining cases were less than six. However, eight cases are considered to have a low level of participation in e-government, with a score of “0” (no). There were nine cases in the second and third composite conditions, along with 319 cases in the eighth composite condition, and less than six cases represented low levels of participation in e-government. Therefore, this study indicates that the fuzzy set for analyzing high and low levels of participation in e-government is diverse and unique.


### 5.3.2. fsQCA Findings

The results of the fsQCA analysis of intermediate solutions, including core and peripheral conditions, form high and low e-government participation, are presented in Table10. It is evident from the solutions that two configurations exist that describe “high” and “low” levels of e-government participation. Ragin [72] recommended that the consistency value for “high” levels of overall results is more significant than 0.75, which indicates a combination of causal conditions that are highly relevant and acceptable. For high e-government participation outcomes, the overall solution consistency value is 0.973, and the overall solution coverage value is 0.878, and for “low” e-government participation outcomes, the overall consistency value is 0.769, and the overall solution coverage value is 0.879. This score reflects a better prediction for both results of “high” and “low” participation in e-government activities.Table 10
Configuration for “high” and “low” e-government participation.
ConfigurationHigh e-government participationLow e-government participationP1P2P3P4Trust to e-government (TTE)●●Social mediaInformation quality (IQ)●●Perceived ease of use (PEOU)●●⨂Perceived usefulness (PU)●●⨂Good governanceTransparency (TR)●Accountability (AT)Responsiveness (RV)●Raw coverage0.8240.8200.7950.800Unique coverage0.0300.0260.0150.017Consistency0.9800.9810.9820.982Overall solution coverage0.8780.879Overall solution consistency0.9730.769Note: black circle (●) indicates the presence of condition; a circle with a cross (⨂) indicates the absence of condition; blank column shows “do not care” condition.Figures4 and 5 present the results of the fsQCA configuration with high consistency and relevance to form high participation in e-government. The entire configurations lead to “presence” (∗) conditions and are unique, thus supporting Proposition 1. Further, the first path (P1) for outcome high e-government participation is moulded by combining the “presence” conditions of ∗TTE, ∗IQ, ∗PEOU, ∗PU, ∗RV, and “do not care” conditions of TP and AT (consistency=0.980 and coverage=0.824). The results from path 1 illustrate how trust in e-government is an essential predictor of increasing e-government participation in e-government use. As a result, trust is formed by social media, which contains high-quality e-government information, perceived ease of use, perceived usefulness, and good governance, namely, the responsiveness of the government to the public. The second configuration (P2), which incorporates “presence” conditions of ∗TTE, ∗IQ, ∗PEOU, ∗PU, ∗TP, and “do not care” condition for AT and RV, also results in a high level of e-government participation (consistency=0.981 and coverage=0.820).Figure 4
Path 1 contributes to high e-government participation (HEP) (consistency=0.980 and coverage=0.824). Note: the solid ellipse represents the presence of the condition. If no ellipse is displayed, it belongs to the “do not care” condition.Figure 5
Path 2 contributes to high e-government participation (HEP) (consistency=0.981 and coverage=0.820). Note: the solid ellipse represents the presence of the condition. If no ellipse is displayed, it belongs to the “do not care” condition.As shown in Figures6 and 7, the results of the fsQCA configuration with a high level of consistency and relevance for a “low” level of e-government participation are visualized. The results demonstrate that overall solution coverage is 0.879 and solution consistency is 0.769, which follows Ragin’s [72] recommendations. Results of the study demonstrate that a configurational path with “low” e-government participation can be derived from a combination of trust, social media, and good governance, thus supporting Proposition 2. In more detail, the configuration (P3 and P4) produces a combination of “absence” and “do not care” conditions. The configurational path 3 (P3) shows an “absence” (~) condition of perceived ease of use (~PEOU) and “do not care” conditions of TTE, IQ, PU, TR, AT, and RV with a higher relevance value than the other configurations (consistency=0.982 and coverage=0.810). This indicates that the information of e-government on social media still needs to be flexible to use and cannot satisfy the public’s electronic and informational needs. This ultimately results in a low level of participation in e-government. Furthermore, the fourth configuration (P4) demonstrates an absence of perceived usefulness (~PU) and “do not care” conditions of TTE, IQ, PEOU, TR, A, and RV condition with a high relevance value (consistency=0.982 and coverage=0.795). This configuration shows that the benefits of PU in e-government information on social media cannot be perceived as valuable by citizens, which results in a low participation rate.Figure 6
Path 3 contributes to low e-government participation (LEP) (consistency=0.982 and coverage=0.795). Note: the dotted ellipse represents the absence of the condition. If no ellipse displayed, it belongs to the “do not care” condition.Figure 7
Path 4 contributes to low e-government participation (LEP) (consistency=0.982 and coverage=0.800). Note: the dotted ellipse represents the absence of the condition. If no ellipse displayed, it belongs to the “do not care” condition.


## 5.3.1. Calibration Selection and Truth Table Construction

This study uses fsQCA analysis to produce high and low e-government participation configurations as outcome variables moulded from the constructs of trust in e-government, social media (information quality, perceived ease of use, and perceived usefulness), and good governance (transparency, responsiveness, and accountability). This study will use the analysis results to resolve a complex issue developing from interdimensional relationships between constructs in the research model. First, in order to transform the data, Pappas and Woodside [70] advocate calibrating the seven-Likert scale into three groups (“6” indicates a full membership, “4” indicates the intersection or median, and “2” indicates a full nonmembership). Therefore, the calibrated data then converts to fuzzy scores of “0”, “low,” and “1”, “high,” and arranged in a truth table that represents entire possible composite conditions that reproduce “high” and “low” participation in e-government. The calibration results are presented in Tables 8 and 9.Table 8
Truth table for high e-government participation.
Antecedents for high e-government participationIQPEOUPURVATTPTTECasesOutcome for high e-government participationRaw consistency11101113Yes0.99711111016Yes0.99611100114Yes0.99501111119Yes0.99211110114Yes0.99011111103Yes0.98811110016Yes0.9871111111319Yes0.985Notes: IQ: information quality; PEOU: perceived ease of use; PU: perceived usefulness; RV: responsiveness; AT: accountability; TP: transparency; TTE: trust to e-government; EP: e-government participation.Table 9
Truth table for low e-government participation.
Antecedents for low e-government participationIQPEOUPURVATTPTTECasesOutcome for low e-government participationRaw consistency11111103No0.77311110016No0.73411100114No0.73611110114No0.70501111119No0.68711101113No0.66511111016No0.6651111111319No0.203Notes: IQ: information quality; PEOU: perceived ease of use; PU: perceived usefulness; RV: responsiveness; AT: accountability; TP: transparency; TTE: trust to e-government; EP: e-government participation.According to a truth table analysis, eight composite indicators with scores of “1” (yes) indicate a high level of participation in e-government. In particular, there were nine cases in the fifth composite and 319 cases in the eighth composite, while the remaining cases were less than six. However, eight cases are considered to have a low level of participation in e-government, with a score of “0” (no). There were nine cases in the second and third composite conditions, along with 319 cases in the eighth composite condition, and less than six cases represented low levels of participation in e-government. Therefore, this study indicates that the fuzzy set for analyzing high and low levels of participation in e-government is diverse and unique.


## 5.3.2. fsQCA Findings

The results of the fsQCA analysis of intermediate solutions, including core and peripheral conditions, form high and low e-government participation, are presented in Table10. It is evident from the solutions that two configurations exist that describe “high” and “low” levels of e-government participation. Ragin [72] recommended that the consistency value for “high” levels of overall results is more significant than 0.75, which indicates a combination of causal conditions that are highly relevant and acceptable. For high e-government participation outcomes, the overall solution consistency value is 0.973, and the overall solution coverage value is 0.878, and for “low” e-government participation outcomes, the overall consistency value is 0.769, and the overall solution coverage value is 0.879. This score reflects a better prediction for both results of “high” and “low” participation in e-government activities.Table 10
Configuration for “high” and “low” e-government participation.
ConfigurationHigh e-government participationLow e-government participationP1P2P3P4Trust to e-government (TTE)●●Social mediaInformation quality (IQ)●●Perceived ease of use (PEOU)●●⨂Perceived usefulness (PU)●●⨂Good governanceTransparency (TR)●Accountability (AT)Responsiveness (RV)●Raw coverage0.8240.8200.7950.800Unique coverage0.0300.0260.0150.017Consistency0.9800.9810.9820.982Overall solution coverage0.8780.879Overall solution consistency0.9730.769Note: black circle (●) indicates the presence of condition; a circle with a cross (⨂) indicates the absence of condition; blank column shows “do not care” condition.Figures4 and 5 present the results of the fsQCA configuration with high consistency and relevance to form high participation in e-government. The entire configurations lead to “presence” (∗) conditions and are unique, thus supporting Proposition 1. Further, the first path (P1) for outcome high e-government participation is moulded by combining the “presence” conditions of ∗TTE, ∗IQ, ∗PEOU, ∗PU, ∗RV, and “do not care” conditions of TP and AT (consistency=0.980 and coverage=0.824). The results from path 1 illustrate how trust in e-government is an essential predictor of increasing e-government participation in e-government use. As a result, trust is formed by social media, which contains high-quality e-government information, perceived ease of use, perceived usefulness, and good governance, namely, the responsiveness of the government to the public. The second configuration (P2), which incorporates “presence” conditions of ∗TTE, ∗IQ, ∗PEOU, ∗PU, ∗TP, and “do not care” condition for AT and RV, also results in a high level of e-government participation (consistency=0.981 and coverage=0.820).Figure 4
Path 1 contributes to high e-government participation (HEP) (consistency=0.980 and coverage=0.824). Note: the solid ellipse represents the presence of the condition. If no ellipse is displayed, it belongs to the “do not care” condition.Figure 5
Path 2 contributes to high e-government participation (HEP) (consistency=0.981 and coverage=0.820). Note: the solid ellipse represents the presence of the condition. If no ellipse is displayed, it belongs to the “do not care” condition.As shown in Figures6 and 7, the results of the fsQCA configuration with a high level of consistency and relevance for a “low” level of e-government participation are visualized. The results demonstrate that overall solution coverage is 0.879 and solution consistency is 0.769, which follows Ragin’s [72] recommendations. Results of the study demonstrate that a configurational path with “low” e-government participation can be derived from a combination of trust, social media, and good governance, thus supporting Proposition 2. In more detail, the configuration (P3 and P4) produces a combination of “absence” and “do not care” conditions. The configurational path 3 (P3) shows an “absence” (~) condition of perceived ease of use (~PEOU) and “do not care” conditions of TTE, IQ, PU, TR, AT, and RV with a higher relevance value than the other configurations (consistency=0.982 and coverage=0.810). This indicates that the information of e-government on social media still needs to be flexible to use and cannot satisfy the public’s electronic and informational needs. This ultimately results in a low level of participation in e-government. Furthermore, the fourth configuration (P4) demonstrates an absence of perceived usefulness (~PU) and “do not care” conditions of TTE, IQ, PEOU, TR, A, and RV condition with a high relevance value (consistency=0.982 and coverage=0.795). This configuration shows that the benefits of PU in e-government information on social media cannot be perceived as valuable by citizens, which results in a low participation rate.Figure 6
Path 3 contributes to low e-government participation (LEP) (consistency=0.982 and coverage=0.795). Note: the dotted ellipse represents the absence of the condition. If no ellipse displayed, it belongs to the “do not care” condition.Figure 7
Path 4 contributes to low e-government participation (LEP) (consistency=0.982 and coverage=0.800). Note: the dotted ellipse represents the absence of the condition. If no ellipse displayed, it belongs to the “do not care” condition.


## 6. Conclusion

### 6.1. Main Findings

This study seeks to examine the factors that influence public participation in e-government and determine whether the research model can be effectively implemented to enforce a deliberative policy. According to previous literature, social media and good governance are key factors contributing to enhanced public participation in the effective implementation of e-government [18, 40]. This study examines how social media factors (information quality, perceived ease of use, and perceived usefulness) and good governance factors (transparency, accountability, and responsiveness) impact trust in e-government. According to this research model, trust plays a significant role in influencing the conversion of the factors forming trust into the outcome of trust, namely, e-government participation [40]. Based on the study’s findings, the following discussion was apprehended, using the deliberative policy theory to test a research model with respondents who were knowledgeable about and actively involved in e-government implementation in Indonesia.This study examines the relationship between trust on e-government participation. The results indicate that citizens’ trust significantly influences e-government participation (H1). This suggests that citizens’ trust is critical in determining their participation in e-government. As a result, a higher level of participation in e-government will result from the awareness of the risk and uncertainty associated with e-government [73]. This finding is consistent with Khan et al. [40], who found that trust in e-government significantly impacts participation. Furthermore, social media has been shown to facilitate government interaction with the community regarding quality information, perceived ease of use, and perceived usefulness of government information. Information quality refers to citizen’s perceptions of the accuracy, completeness, and usability of e-government information sources [47]. According to the analysis, it indicates no significant impact of information quality on trust in e-government services (H2a). The results indicate that citizens’ use of social media as a source of information about e-government is ineffective in improving trust in e-government; therefore, social media does not provide information quality that can meet the needs of citizens about e-government. This finding is in line with Porumbescu [55], which states that exposure to social media that contains more detailed information often generates critical responses and dissatisfaction, which causes low e-government participation.Information provided by e-government that is flexible and user-friendly without any restrictions is referred to as perceived ease of use [49, 50]. According to the study, a significant proportion of trust in e-government is influenced by perceived ease of use (H2b). This finding suggests that citizens perceive social media as easy to find information about e-government. Thus, when social media is considered easy for citizens to find information about e-government, they tend to trust e-government. Thus, e-government services will be more likely to be used by users if the service is easy to use, resulting in greater general trust in the system. The result is consistent with previous findings [40]. Perceived usefulness refers to e-government information that promotes effectiveness, performance, and community benefit. In this study, it was found that perceived usefulness significantly influences trust in e-government (H2c). This finding confirms that when citizens find e-government information on social media valuable and insightful, it will lead them to trust in e-government. Furthermore, trust in e-government increases when e-government information is considered beneficial to society. Additionally, Abu-Shanab [51] confirms that perceived usefulness affects trust in e-government significantly.Furthermore, implementing deliberative policies through e-government can be achieved by providing good governance characterized by transparency, accountability, and responsiveness [18]. Transparency refers to the availability of pertinent information about government performance procedures and transparent decision-making processes regarding public policy. According to analysis, transparency (H3a) is associated with a substantial increase in trust in e-government. This finding suggests that the government demonstrated good transparency in implementing e-government instruments for the community, which will likely increase the citizens’ trust. As a result, public understanding is increased by submitting consistent, comprehensive, and transparent performance information from the government, leading to increased trust among the public. Previous research has confirmed these findings [18]. Moreover, accountability refers to the government’s responsibility to manage policies effectively, efficiently, and economically. Hypothesis testing indicates that accountability (H3b) has no significant effect on trust in e-government. This finding suggests that the government is not accountable when conducting its instrument of e-government to the public. Therefore, the citizens perform disbelieve or are reluctant to trust in e-government. Additionally, the government cannot demonstrate effective, efficient, and economic management of policies for the community, resulting in low trust in e-government [74]. Furthermore, the responsiveness dimension considers how well the government responds to the local community’s ideas, opinions, and demands. The analysis indicates that responsiveness (H3c) has no significant effect on trust in e-government. This finding confirms that citizens (Indonesian) perceived the government as not highly responsive to respond to the needs of citizens to use e-government. Due to this, the government’s inability to respond speedily to citizens’ requests results in a low level of trust in e-government.According to configurational analysis, the complexity of theory emphasizes the outcomes of high and low levels of e-government participation based on predictors of trust in e-government, social media dimensions (information quality, perceived ease of use, and perceived usefulness), and good governance dimensions. There are two solutions to achieve high levels of e-government participation based on high levels of participation in e-government. Additionally, each configuration exhibits high consistency and coverage, indicating that each solution represents the conditions necessary for implementing high levels of e-government. For high e-government participation, configurational path one (P1) is the best and inimitable, which indicates that high e-government participation will be achieved through emphasizing trust in e-government, information quality, perceived ease of use, and perceived usefulness. Although other constructs seem to be “do not care,” it does not have an impactful effect on increasing participation. Furthermore, this study measures the results of low citizen participation in e-government. A key factor determining the causes of low e-government participation is the lack of perceived ease of use of configuration path four (P4), which indicates that the government “do not care” about good governance and social media factors (perceived usefulness and information quality); the citizens will not participate with e-government. In this sense, it is essential to practice and give information related to e-government through social media to citizens.


#### 6.1.1. Theoretical Implications

This study gives knowledge to the existing literature about how citizens can participate in e-government. By establishing a framework model based on deliberative policy theory, this study provides insights into the new planning strategy for government based on public interest. The conceptual model employs a deliberative process that emphasizes the needs and interests of the public in order to enhance the effectiveness of e-government participation [26]. This study examines e-government participation using trust in e-government as a mechanism between social media and good governance. In this study, trust in e-government is demonstrated to increase participation in e-government significantly. Thus, the trust formed impacts community participation, which impacts the effectiveness of public policy implementation.This study examines three social media factors to increase trust in e-government: information quality, perceived ease of use, and perceived usefulness. A significant amount of trust in e-government is boosted by perceived ease of use and usefulness. However, the dimensions of information quality do not show significant effects. Therefore, e-government information on social media is flexible, easy to use, and beneficial to society, as demonstrated by this study. Additionally, this study identifies good governance factors such as transparency, accountability, and responsiveness to increase trust in e-government.On the other hand, the dimensions of transparency and accountability are insignificant, but they promote trust in e-government. The availability of government performance information in a consistent, complete, and transparent manner contributes to public understanding, affecting trust [18, 57]. In conclusion, this study’s results indicate that both social media and good governance have a significant positive impact on e-government participation.In order to maximize public participation effectiveness, researchers can integrate trust in e-government, social media dimensions, and good governance into the results of the QCA configuration analysis by integrating e-government services. The causal condition configuration for both high and low e-government participation outcomes was determined based on the theoretical complexity achieved in this study. According to the findings of this study, there are two configurations of e-government participation solutions, and therefore, a theoretical foundation can be established for future studies aimed at increasing participation in e-government.


#### 6.1.2. e-Government Practice

The study also contributes to e-government practice. This is especially true when the government defines a strategy for enhancing e-government participation through social media use and ensuring good governance in public service delivery. As current information and communication technologies (ICTs) become more popular among citizens, governments can boost efficiency, improve service quality, and increase democratic participation [6, 75]. Investigating social media and good governance factors as forming trust towards e-government will have implications for increasing e-government participation, which will benefit governments across the board. For example, this study applied to Indonesia and discovered a way to improve public participation through e-government while assessing whether the policies had been effectively implemented [76]. Based on these results, a strategy to increase public participation in e-government services is expected to be developed.This study has found that perceived ease of use and usefulness significantly increase trust in e-government. In other words, e-government information on social media is regarded as flexible, easy to use, and beneficial to society. Furthermore, transparency is a significant factor in encouraging trust in electronic government. Providing government performance information consistently, entirely, and transparently to the public is crucial to building trust and forming a public understanding. Consequently, the results of this study have confirmed that social media factors (perceived ease of use and perceived usefulness) and good governance (transparency) in e-government services contribute to increased participation in e-government services. Through the public’s participation, the government can obtain valuable advice and opinions that will enable them to make more appropriate public policy decisions [77]. In addition, fsQCA results provide government officials with valuable insights into improving the quality of their public services. Each configuration presents a different combination that will result in a high or low e-government participation rate. This study suggests that a combination of configuration path one (P1) for high e-government participation and configuration path four (P4) to avoid low e-government participation can be applied to identify future levels of community participation in public services. Through this combination of channels, the government can improve the quality of its public services and make decisions that benefit both sides.


#### 6.1.3. Limitation and Future Research

Despite its significant theoretical contributions and exposure to e-government practices, this study has several limitations. First, this study is limited by the trust and participation formed due to e-government implementation. According to Belanche et al. [63] and Abdulkareem et al. [78], it has been found that trust has a positive relationship with community satisfaction and continued intention to use e-government. Therefore, future research is expected to investigate whether the trust is associated with community satisfaction and intention to continue using e-government. Second, the study uses data from Indonesian respondents that cannot be generalized to other countries. Because e-government has become increasingly popular in many countries, this study provides only a perspective on e-government participation in Indonesian society. Therefore, future research should generalize sample areas, for example, from the perspective of developed and developing countries. Finally, this study examines e-government participation as an implication of deliberative policy from the perspective of social media, good governance, and trust resulting from the deliberative policy. Deliberative policy, however, continues to have a broad application in achieving public participation in government policy, even today.


## 6.1. Main Findings

This study seeks to examine the factors that influence public participation in e-government and determine whether the research model can be effectively implemented to enforce a deliberative policy. According to previous literature, social media and good governance are key factors contributing to enhanced public participation in the effective implementation of e-government [18, 40]. This study examines how social media factors (information quality, perceived ease of use, and perceived usefulness) and good governance factors (transparency, accountability, and responsiveness) impact trust in e-government. According to this research model, trust plays a significant role in influencing the conversion of the factors forming trust into the outcome of trust, namely, e-government participation [40]. Based on the study’s findings, the following discussion was apprehended, using the deliberative policy theory to test a research model with respondents who were knowledgeable about and actively involved in e-government implementation in Indonesia.This study examines the relationship between trust on e-government participation. The results indicate that citizens’ trust significantly influences e-government participation (H1). This suggests that citizens’ trust is critical in determining their participation in e-government. As a result, a higher level of participation in e-government will result from the awareness of the risk and uncertainty associated with e-government [73]. This finding is consistent with Khan et al. [40], who found that trust in e-government significantly impacts participation. Furthermore, social media has been shown to facilitate government interaction with the community regarding quality information, perceived ease of use, and perceived usefulness of government information. Information quality refers to citizen’s perceptions of the accuracy, completeness, and usability of e-government information sources [47]. According to the analysis, it indicates no significant impact of information quality on trust in e-government services (H2a). The results indicate that citizens’ use of social media as a source of information about e-government is ineffective in improving trust in e-government; therefore, social media does not provide information quality that can meet the needs of citizens about e-government. This finding is in line with Porumbescu [55], which states that exposure to social media that contains more detailed information often generates critical responses and dissatisfaction, which causes low e-government participation.Information provided by e-government that is flexible and user-friendly without any restrictions is referred to as perceived ease of use [49, 50]. According to the study, a significant proportion of trust in e-government is influenced by perceived ease of use (H2b). This finding suggests that citizens perceive social media as easy to find information about e-government. Thus, when social media is considered easy for citizens to find information about e-government, they tend to trust e-government. Thus, e-government services will be more likely to be used by users if the service is easy to use, resulting in greater general trust in the system. The result is consistent with previous findings [40]. Perceived usefulness refers to e-government information that promotes effectiveness, performance, and community benefit. In this study, it was found that perceived usefulness significantly influences trust in e-government (H2c). This finding confirms that when citizens find e-government information on social media valuable and insightful, it will lead them to trust in e-government. Furthermore, trust in e-government increases when e-government information is considered beneficial to society. Additionally, Abu-Shanab [51] confirms that perceived usefulness affects trust in e-government significantly.Furthermore, implementing deliberative policies through e-government can be achieved by providing good governance characterized by transparency, accountability, and responsiveness [18]. Transparency refers to the availability of pertinent information about government performance procedures and transparent decision-making processes regarding public policy. According to analysis, transparency (H3a) is associated with a substantial increase in trust in e-government. This finding suggests that the government demonstrated good transparency in implementing e-government instruments for the community, which will likely increase the citizens’ trust. As a result, public understanding is increased by submitting consistent, comprehensive, and transparent performance information from the government, leading to increased trust among the public. Previous research has confirmed these findings [18]. Moreover, accountability refers to the government’s responsibility to manage policies effectively, efficiently, and economically. Hypothesis testing indicates that accountability (H3b) has no significant effect on trust in e-government. This finding suggests that the government is not accountable when conducting its instrument of e-government to the public. Therefore, the citizens perform disbelieve or are reluctant to trust in e-government. Additionally, the government cannot demonstrate effective, efficient, and economic management of policies for the community, resulting in low trust in e-government [74]. Furthermore, the responsiveness dimension considers how well the government responds to the local community’s ideas, opinions, and demands. The analysis indicates that responsiveness (H3c) has no significant effect on trust in e-government. This finding confirms that citizens (Indonesian) perceived the government as not highly responsive to respond to the needs of citizens to use e-government. Due to this, the government’s inability to respond speedily to citizens’ requests results in a low level of trust in e-government.According to configurational analysis, the complexity of theory emphasizes the outcomes of high and low levels of e-government participation based on predictors of trust in e-government, social media dimensions (information quality, perceived ease of use, and perceived usefulness), and good governance dimensions. There are two solutions to achieve high levels of e-government participation based on high levels of participation in e-government. Additionally, each configuration exhibits high consistency and coverage, indicating that each solution represents the conditions necessary for implementing high levels of e-government. For high e-government participation, configurational path one (P1) is the best and inimitable, which indicates that high e-government participation will be achieved through emphasizing trust in e-government, information quality, perceived ease of use, and perceived usefulness. Although other constructs seem to be “do not care,” it does not have an impactful effect on increasing participation. Furthermore, this study measures the results of low citizen participation in e-government. A key factor determining the causes of low e-government participation is the lack of perceived ease of use of configuration path four (P4), which indicates that the government “do not care” about good governance and social media factors (perceived usefulness and information quality); the citizens will not participate with e-government. In this sense, it is essential to practice and give information related to e-government through social media to citizens.


### 6.1.1. Theoretical Implications

This study gives knowledge to the existing literature about how citizens can participate in e-government. By establishing a framework model based on deliberative policy theory, this study provides insights into the new planning strategy for government based on public interest. The conceptual model employs a deliberative process that emphasizes the needs and interests of the public in order to enhance the effectiveness of e-government participation [26]. This study examines e-government participation using trust in e-government as a mechanism between social media and good governance. In this study, trust in e-government is demonstrated to increase participation in e-government significantly. Thus, the trust formed impacts community participation, which impacts the effectiveness of public policy implementation.This study examines three social media factors to increase trust in e-government: information quality, perceived ease of use, and perceived usefulness. A significant amount of trust in e-government is boosted by perceived ease of use and usefulness. However, the dimensions of information quality do not show significant effects. Therefore, e-government information on social media is flexible, easy to use, and beneficial to society, as demonstrated by this study. Additionally, this study identifies good governance factors such as transparency, accountability, and responsiveness to increase trust in e-government.On the other hand, the dimensions of transparency and accountability are insignificant, but they promote trust in e-government. The availability of government performance information in a consistent, complete, and transparent manner contributes to public understanding, affecting trust [18, 57]. In conclusion, this study’s results indicate that both social media and good governance have a significant positive impact on e-government participation.In order to maximize public participation effectiveness, researchers can integrate trust in e-government, social media dimensions, and good governance into the results of the QCA configuration analysis by integrating e-government services. The causal condition configuration for both high and low e-government participation outcomes was determined based on the theoretical complexity achieved in this study. According to the findings of this study, there are two configurations of e-government participation solutions, and therefore, a theoretical foundation can be established for future studies aimed at increasing participation in e-government.


### 6.1.2. e-Government Practice

The study also contributes to e-government practice. This is especially true when the government defines a strategy for enhancing e-government participation through social media use and ensuring good governance in public service delivery. As current information and communication technologies (ICTs) become more popular among citizens, governments can boost efficiency, improve service quality, and increase democratic participation [6, 75]. Investigating social media and good governance factors as forming trust towards e-government will have implications for increasing e-government participation, which will benefit governments across the board. For example, this study applied to Indonesia and discovered a way to improve public participation through e-government while assessing whether the policies had been effectively implemented [76]. Based on these results, a strategy to increase public participation in e-government services is expected to be developed.This study has found that perceived ease of use and usefulness significantly increase trust in e-government. In other words, e-government information on social media is regarded as flexible, easy to use, and beneficial to society. Furthermore, transparency is a significant factor in encouraging trust in electronic government. Providing government performance information consistently, entirely, and transparently to the public is crucial to building trust and forming a public understanding. Consequently, the results of this study have confirmed that social media factors (perceived ease of use and perceived usefulness) and good governance (transparency) in e-government services contribute to increased participation in e-government services. Through the public’s participation, the government can obtain valuable advice and opinions that will enable them to make more appropriate public policy decisions [77]. In addition, fsQCA results provide government officials with valuable insights into improving the quality of their public services. Each configuration presents a different combination that will result in a high or low e-government participation rate. This study suggests that a combination of configuration path one (P1) for high e-government participation and configuration path four (P4) to avoid low e-government participation can be applied to identify future levels of community participation in public services. Through this combination of channels, the government can improve the quality of its public services and make decisions that benefit both sides.


### 6.1.3. Limitation and Future Research

Despite its significant theoretical contributions and exposure to e-government practices, this study has several limitations. First, this study is limited by the trust and participation formed due to e-government implementation. According to Belanche et al. [63] and Abdulkareem et al. [78], it has been found that trust has a positive relationship with community satisfaction and continued intention to use e-government. Therefore, future research is expected to investigate whether the trust is associated with community satisfaction and intention to continue using e-government. Second, the study uses data from Indonesian respondents that cannot be generalized to other countries. Because e-government has become increasingly popular in many countries, this study provides only a perspective on e-government participation in Indonesian society. Therefore, future research should generalize sample areas, for example, from the perspective of developed and developing countries. Finally, this study examines e-government participation as an implication of deliberative policy from the perspective of social media, good governance, and trust resulting from the deliberative policy. Deliberative policy, however, continues to have a broad application in achieving public participation in government policy, even today.


## 6.1.1. Theoretical Implications

This study gives knowledge to the existing literature about how citizens can participate in e-government. By establishing a framework model based on deliberative policy theory, this study provides insights into the new planning strategy for government based on public interest. The conceptual model employs a deliberative process that emphasizes the needs and interests of the public in order to enhance the effectiveness of e-government participation [26]. This study examines e-government participation using trust in e-government as a mechanism between social media and good governance. In this study, trust in e-government is demonstrated to increase participation in e-government significantly. Thus, the trust formed impacts community participation, which impacts the effectiveness of public policy implementation.This study examines three social media factors to increase trust in e-government: information quality, perceived ease of use, and perceived usefulness. A significant amount of trust in e-government is boosted by perceived ease of use and usefulness. However, the dimensions of information quality do not show significant effects. Therefore, e-government information on social media is flexible, easy to use, and beneficial to society, as demonstrated by this study. Additionally, this study identifies good governance factors such as transparency, accountability, and responsiveness to increase trust in e-government.On the other hand, the dimensions of transparency and accountability are insignificant, but they promote trust in e-government. The availability of government performance information in a consistent, complete, and transparent manner contributes to public understanding, affecting trust [18, 57]. In conclusion, this study’s results indicate that both social media and good governance have a significant positive impact on e-government participation.In order to maximize public participation effectiveness, researchers can integrate trust in e-government, social media dimensions, and good governance into the results of the QCA configuration analysis by integrating e-government services. The causal condition configuration for both high and low e-government participation outcomes was determined based on the theoretical complexity achieved in this study. According to the findings of this study, there are two configurations of e-government participation solutions, and therefore, a theoretical foundation can be established for future studies aimed at increasing participation in e-government.


## 6.1.2. e-Government Practice

The study also contributes to e-government practice. This is especially true when the government defines a strategy for enhancing e-government participation through social media use and ensuring good governance in public service delivery. As current information and communication technologies (ICTs) become more popular among citizens, governments can boost efficiency, improve service quality, and increase democratic participation [6, 75]. Investigating social media and good governance factors as forming trust towards e-government will have implications for increasing e-government participation, which will benefit governments across the board. For example, this study applied to Indonesia and discovered a way to improve public participation through e-government while assessing whether the policies had been effectively implemented [76]. Based on these results, a strategy to increase public participation in e-government services is expected to be developed.This study has found that perceived ease of use and usefulness significantly increase trust in e-government. In other words, e-government information on social media is regarded as flexible, easy to use, and beneficial to society. Furthermore, transparency is a significant factor in encouraging trust in electronic government. Providing government performance information consistently, entirely, and transparently to the public is crucial to building trust and forming a public understanding. Consequently, the results of this study have confirmed that social media factors (perceived ease of use and perceived usefulness) and good governance (transparency) in e-government services contribute to increased participation in e-government services. Through the public’s participation, the government can obtain valuable advice and opinions that will enable them to make more appropriate public policy decisions [77]. In addition, fsQCA results provide government officials with valuable insights into improving the quality of their public services. Each configuration presents a different combination that will result in a high or low e-government participation rate. This study suggests that a combination of configuration path one (P1) for high e-government participation and configuration path four (P4) to avoid low e-government participation can be applied to identify future levels of community participation in public services. Through this combination of channels, the government can improve the quality of its public services and make decisions that benefit both sides.


## 6.1.3. Limitation and Future Research

Despite its significant theoretical contributions and exposure to e-government practices, this study has several limitations. First, this study is limited by the trust and participation formed due to e-government implementation. According to Belanche et al. [63] and Abdulkareem et al. [78], it has been found that trust has a positive relationship with community satisfaction and continued intention to use e-government. Therefore, future research is expected to investigate whether the trust is associated with community satisfaction and intention to continue using e-government. Second, the study uses data from Indonesian respondents that cannot be generalized to other countries. Because e-government has become increasingly popular in many countries, this study provides only a perspective on e-government participation in Indonesian society. Therefore, future research should generalize sample areas, for example, from the perspective of developed and developing countries. Finally, this study examines e-government participation as an implication of deliberative policy from the perspective of social media, good governance, and trust resulting from the deliberative policy. Deliberative policy, however, continues to have a broad application in achieving public participation in government policy, even today.



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*Source: 9988602-2023-02-16.xml*