THE RELATIONSHIP BETWEEN DIGITIZATION OF GOVERNMENTAL SERVICES IN THE NETHERLANDS AND PUBLIC TRUST IN GOVERNMENT
by Kim Baeten
A thesis submitted to the Graduate School of Communication in partial fulfillment of the requirements for the degree
of Master of Science in Communication Science
Supervisor - Dr. Piet Verhoeven February 2018
Abstract
The use of information and communication technologies (ICTs) has changed the way
organizations communicate with their stakeholders. The same is true for government services in the Netherlands, which keep expanding their use of so-called e-government to make transactions between government and the public go faster, more efficiently, and cheaper. However, reports show that the public does not always view e-government as a positive development and does not always intent to use it. This study used computer mediated communication (CMC) theories to discover what stimulates citizens to want to use e-government websites (perceived usefulness of the websites, perceived ease of use of the websites and trust in technology) and also looks at the effect this intention to use
e-government websites has on citizens’ overall trust in e-government. SPSS analysis of online survey results showed that intention to use e-government websites revealed that intention to use e-government websites functioned as a mediator between trust in government and the three stimuli variables. It appears that if government services want citizens to use their e-government websites and thus win their trust, they should make these websites easy to use, safe to use and emphasis the usefulness and importance of e-government.
Introduction Defining e-government
Over the last 20 years, information and communication technologies (ICTs) have greatly changed the way humans communicate and interact with each other. ICTs have allowed people to communicate on a global scale and to do a lot of things faster and more efficiently. In addition to changing the way people communicate in their daily lives, ICTs have also changed the way organizations function and communicate. Most existing literature on the use of ICTs in organizations is positive: ICTs are believed promote economic benefits like efficiency, cost savings and competitiveness. However, there is increasing anxiety over the societal effects that digitalization can have, such as socioeconomic polarization
(Nieminen, 2015). ICTs are often believed to promote economic benefits, such as efficiency, cost savings and competitiveness for the organizations using them (Nieminen, 2015).
Digitalization allows organizations to communicate faster, more effectively and cheaper towards stakeholders (“Digitaal 2017”, 2017).
While most types of organizations have already embraced digitization and the use of ICTs, governments are now starting to make the switch from paper communication to digital communication and are trying to find innovative digital solutions to social, economic, and other pressures. The digital revolution is changing interactions between governments and citizens and so-called e-governments have started as new channels of communication. E-government can be defined as “the use of information and communications technology, particularly the Internet, for the delivery of public services (Horsburgh, Goldfinch, & Gauld, 2011)”. E-government redefines existing and new information, communication and
transaction-related interactions with stakeholders through ICTs, with the purpose of improving government performance and processes (Chun et al, 2010). ICTs offers governments the opportunity to speed up work processes, increase the effectiveness and efficiency of work, offer better and more customized services, and lighten the load of
bureaucracy (Prins, Broeders, & Griffioen, 2012). According to Prins, Broeders, & Griffioen (p. 273) e-government “makes government streamlined, digital and service-minded while at the same time catering to the needs of the citizen and ‘client’.”
Chun et al. (2010) define three different stages of e-government evolution. The first stage of e-government focuses on digital presence. This stage includes Web sites of a passive nature that simply provide government information. The second stage provides simple
Web-based interactions of governments with citizens. These interactions can occur via email contact or interactive forms. The final stage provides online transaction services, such as permit applications. Chun et al. acknowledge that e-government communication so-far has mainly been flowing in one direction: from the government to the public.
E-government in The Netherlands
Government in The Netherlands strongly values the digitization of government services. Cabinet Rutte II created the program “Digitaal 2017” (Digital 2017) in which it formulated their ambitions for the advancement and improvement of government
digitalization. A 2013 letter by former minister Plasterk to the Chairman of the Dutch House of Representatives summarizes the governments ambitions regarding digitization: a
demonstrable improvement in the quality of digital government information and government services, with attention for those people who are less digitally skilled; considerably less administrative burdens for citizens; important efficiency gains that allow departmental targets to be achieved more easily. A 2016 progress report stated that approximately 550
government-wide services were now available online (88%). E-government includes all kinds of government branches: national organization, provinces, municipalities, hospitals, police, etc. Most of these online activities happen through DigiD, a type of overarching
e-government service. Activities include things like online tax returns, applying for child benefits, matterns concerning your health insurance, registering as an organ donor, applying for financial aid, etc. (“Digitaal 2017”, 2017). In 2006 not even half of Dutch citizens used e-government services. Approximately 45% of Dutch citizens used e-e-government services to find information online, 20% used it to download forms, and only 12% used e-government services to upload forms (Van Kooten & Weller, 2006).
An important development in the digitization of government in The Netherlands is the launch of the online communication platform MijnOverheid.nl (MyGovernment.nl) in 2015. MijnOverheid.nl is used by many government services, including the tax office and the social insurance bank. A 2017 investigation by the ombudsman, however, concluded that the
website does not always work as well as it was intended to. The Ombudsman received around 1,100 complaints since the website was launched two years ago and also found out that many people are not even aware that the website exists (Verhoef et al, 2017).
Linking e-government to trust in government
Trust in government is believed to be related to the effectiveness of government. A government that faces mistrust and suspicion may find that citizens are more likely to resists its actions and are suspicious of its pronouncements and policies (Horsburgh, Goldfinch, & Gauld, 2011).
Research results vary for research done on the relationship between e-government and trust in government. Carter and Bélanger (2005) conclude in their research that perceived ease of use, compatibility and trustworthiness are signification indicators of citizens’ intention to use e-government services. Additionally, Welch, Hinnant, and Jae Moon (2004) conclude that “individuals who are more satisfied with e-government and government Web sites also trust the government more (p. 387)”. Research done by Horsburgh, Goldfinch, and Gauld (2011), however, found no significant relationship between trust in government institutions and various e-government services. Prins, Broeders, and Griffioen (2012) even go as far as to claim that e-government can have a negative effect on trust in government. Prins, Broeders, and Griffioen conclude that a lack of boundaries in data gathering online and a possible lack of trust in security of government websites will eventually undermine the citizen’s confidence in government as a reliable custodian and user of information. Janowski (2015) adds to this that activities in the digital space can amplify existing problems of division, inequity, exclusion, fraud, insecurity, etc. Nieminen (2015) agrees with this by stating that the use of technology can widen the digital divide and sharpen social inequalities on a global scale. In the Netherlands less than 20% of adults above 65 years of age had used the Internet in 2004 (Van Kooten & Weller, 2006). This means that the digitization of government agencies can have negative social consequences for these people.
Taking into account the fast pace in which e-government is developing in the Netherlands and the varying results e-government research have produced, it becomes necessary to study the relationship between e-government and Dutch citizens’ trust in government in more depth. This leads to the following research question:
RQ: How does Dutch citizens’ evaluation of the switch from ‘paper’ government
communication to e-government communication influence their intention to use e-government websites and how does this influence citizens’ trust in government?
With the help of existing literature, a model manifesting possible relationships between the above discussed concepts will be compiled. Subsequently, the model will be empirically tested with the help of an online survey. The results of the survey are going to be presented in a further step and finally the results are going to be discussed in a broader context.
Theoretical framework and hypotheses
In the following theoretical framework the relationships between different core concepts touched on in the introduction will be discussed, using Computer Mediated
Communication (CMC) theories and models as an overarching framework and using findings from previous literature in order to help find the reasons why people intend to use
e-government and the relationship between e-e-government and trust in e-government in the Netherlands. Several hypotheses will be drawn up based on existing literature, which will results in a conceptual model.
The evaluation of e-government services and intention to use e-government websites From previous literature we can conclude that three separate elements of citizens’ evaluation of e-government services lead to the intent to use said e-government services. The three elements are perceived usefulness of the e-government services, perceived ease of use, and trust in technology. The first two elements, perceived usefulness and perceived ease of use, are based on Davis’ (1989) Technology Acceptance Model (TAM). TAM is used to study users acceptance of technology. According to TAM, perceived usefulness and perceived ease of use of a digital system influence one’s attitude towards system usage, which in turn
influences one’s intent to use the system, which is turn determines actual system usage.
Figure 1. Technology Acceptance Model (Davis, 1989).
Carter and Bélanger (2005) use elements of Davis’ TAM, perceived usefulness and perceived ease of use, to see if these are positively related to higher levels of intention to use a state e-government service. Because their variables for measuring perceived usefulness loaded
onto different factors they ended up dropping it from further analysis, but they did find that citizens’ intentions to use a state e-government service will increase if they perceive the service to be easy to use (p. 17). Based on the TAM and Carter and Bélanger’s positive results for at least one of the independent variables in the TAM, this study will use perceived
usefulness and ease of use as variables to measure citizens’ attitude towards e-government services. This leads to the first two hypotheses:
Hypothesis 1: Greater perceived usefulness of e-government services will lead to greater use of e-government websites.
Hypothesis 2: Greater perceived ease of use of e-government services will lead to a greater use of e-government websites.
However, previous research also shows that citizens’ trust in technology and the Internet also plays a role in determining their (intention to) use e-government or ICTs in general. Janowski (2015) concludes that an increase of online activities can risk amplifying existing problems of fraud and insecurity. Fearing the safety of one’s personal information and might restrict citizens’ to use e-government initiatives. Ranaweera (2016) considered, along with elements from the TAM, trustworthiness of the users towards the use of
e-government services as an important antecedent condition for use of e-e-government services. Ranaweera explains that trustworthiness shapes the feelings of the people and plays a crucial role in the acceptance, adoption and use of e-government services (p.1). He used elements like perceived security, perceived privacy, and perceived uncertainty/risk and found that these have an effect on the use of e-government services. Gilbert, Balestrini and Littleboy (2004) also found that safety was one of the perceived barriers for willingness to use e-government services. Carter and Bélanger (2005, p. 15) also concluded in their study that citizens who perceive the reliability and security of the internet to be low will be less likely to adopt e-government services. According to research by Horsburgh, Goldfinch and Gauld (2011) trust in technology and its security are likely to influence use and support for e-government. They believe citizens may be more likely to provide information if they are sure that authorities will not misuse their information and if they believe their information cannot be obtained by private parties through either security failure and/or the corrupt or unauthorized release of information. In this study trust in technology will be defined as the belief citizens have that their personal information is safe on e-government websites, i.e. that they do not risk of fraud,
privacy, or security issues. Taking these findings from previous literature into account allow a third hypothesis to be drawn up:
Hypothesis 3: Greater trust in technology will lead to a greater use of e-government websites. The (intention to) use of e-government services and trust in government
As touched upon in the introduction, citizen trust in government is believed to be related to the effectiveness of government. ‘Trust’ is obviously a concept that is hard to conceptualize, but it has very important implications. Grimmelikhuijsen and Knies (2015, p.587) identify three dimensions to study trust in government organizations that will also be utilized to measure trust in this study:
• Perceived competence: the extent to which a citizen perceives a government organization to be capable, effective, skillful, and professional;
• Perceived benevolence: the extent to which a citizen perceives a government
organization to care about the welfare of the public and to be motivated to act in the public interest; and
• Perceived integrity: the extent to which a citizen perceives a government organization to be sincere, to tell the truth, and to fulfill its promises.
While many studies suggest a positive connection between the use or intention to use e-government and citizen trust in government, there is a lack of empirical evidence to support the claim. There are a few studies that do. Tolbert and Mossberger (2006), for example, claim that e-government has been proposed as a way to increase citizen trust in government because it can restore the public’s faith in the performance of government by providing more open, transparent and efficient ways of communication. Tolbert and Mossberger found that more frequent use of e-government was associated with more positive attitudes toward government processes, but their findings were limited. Welch, Hinnant and Jae Moon (2004, p. 372) suggest that “appropriate utilization of information and communication technologies, especially the internet, by government has the potential to increase citizen satisfaction with government.” They also claim that “better, more convenient services, more accessible and complete information, and new and improved channels of communication may reduce the information gap and improve citizen trust in government (p. 372).” They concluded that those individuals who are more satisfied with e-government and government websites also trust the government more (p. 387).
Computer mediated communication (CMC) uses the internet to mediate for human communication. CMC theories have become integral to studying communication science and the way new forms of communication, including e-government, have an impact on society. They have become integral to the initiation, development, and maintenance of interpersonal relationships (Walther, 2011). CMC theories can also be used to provide a framework for the hypotheses of this study and can lay the groundworks for the claim that the use of
e-government services can improve the political trust of citizens in The Netherlands. While earlier CMC theories believed that CMC has no nonverbal cues and therefore occludes the accomplishment of social functions that those nonverbal cues typically involve. Social Presence Theory, for example, argued that various communication channels differed in their capacity to transmit nonverbal communication, and that CMC could therefore not render any socio-emotional content (Walther, 2011). Walther and Burgoon’s Social Information
Processing Theory (SIP, 1992) that was proposed in their study of the differences in the way people reacted when conveying emotions using face-to-face or computer mediated
communication methods suggests, however, that online interpersonal relationships may demonstrate the same relational dimensions as face-to-face relationships. According to SIP theory, emotions are often conveyed slower using CMCs but the quality of the emotions does not differ (Walther & Burgoon, 1992). Four years later Walther developed the hyperpersonal model of CMC, which explains how CMC may even facilitate impressions and relationships online that exceed the desirability and intimacy that occurs in parallel offline interactions (Walther, 2011, p. 460). When accepting Walther’s CMC theories it can be explained how the use of e-government services can have an emotional impact on users and can allow citizens to feel more confident with, more connected to, and more trusting of the creator of the services: the government.
Taking Walther’s CMC theories as overarching validating theories and looking at the suggestions made in previous literature, the fourth hypothesis is created:
Hypothesis 4: Greater use of e-government services will lead to greater trust in government Since it is hypothesized that perceived usefulness of e-government websites, perceived ease of use of e-government websites and trust in technology will lead to a greater intention to use e-government websites and that intention to use e-government websites will lead to greater trust in government, it can hypothesized that intention to use e-government websites functions as a mediator between the three predictor variables perceived usefulness, perceived ease of
use, trust in technology and outcome variable trust in government. This leads to an additional three hypotheses:
Hypothesis 5: Greater perceived usefulness of e-government websites will lead to greater intention to use e-government websites, which in turn will lead to greater trust in government Hypothesis 6: Greater perceived ease of use of e-government websites will lead to greater intention to use e-government websites, which in turn will lead to greater trust in government Hypothesis 7: Greater trust in technology will lead to greater intention to use e-government websites, which in turn will lead to greater trust in government
All seven hypotheses derived from existing CMC literature can be summarized in a conceptual model:
Figure 2. Conceptual model. Control variables
When looking at the conceptual model, it cannot be denied that other, additional variables may impact the relationship between the different variables. In the analysis of the data the age and ICT experience of the participants will be taken into account as control variables. Nieminen (2016) mentions the threat of a digital divide that comes along with the rise of ICTs. It seems logical to assume that older citizens may find e-government initiatives less easy to use, do not realize its usefulness or potential, or are more threatened by
technological development, which may result in less use of e-government services and thus in less increased trust in government.
Perceived usefulness Perceived ease of use Trust in technology
(Intention to) use e-government
Trust in government
Citizen’s experience with ICT may also influence results. Welch, Hinnant, and Jae Moon found that in their study participants with high internet use were more satisfied with those websites and more trusting of government (2004). Horsburgh, Goldfinch, and Gauld also found an association with technology use and trust in government and various
e-government functions. They explained: “As with driving a car, familiarity with e-mail and the Internet, perhaps, breeds a general confidence in navigating and using the “highway” of e-government services (2011, p. 239).” Additionally, gender and education will be used as control variables.
Methods
In order to investigate the hypotheses as drawn out in the previously described conceptual model, an online quantitative survey has been conducted. In this section, separate subsections will elaborate on the design of the study, the participants, the data cleaning, the factor analysis and reliability analysis for the different variables and the plan for analysis. Design of the study
The survey was designed using the online survey tool “Qualtrics”. Participants were first informed of the purpose of the study and were informed of the ethical guidelines
surrounding the research. In short, participants were guaranteed that their anonymity would be safeguarded, that they were able to refuse participation or stop participation at any time, that they would not be subjected to any type of risk and that, if they were interested, they had the right to view a research report explaining the general results of the study. Subsequently, they were asked if they agreed to participate. The first set of questions asked for the participants’ descriptive characteristics: their age, gender, level of education, and Internet usage. They were then asked to respond to several statements regarding the different variables of the conceptual model. All statements were measured on a 7-point Likert scale ranging from ‘Completely disagree’ to ‘Completely agree’. Several existing scales were used to measure the different constructs used in the model. To measure ‘trust in technology’ existing scales to measure ‘trust of the Internet’ by Carter and Bélanger (2005, p. 25) were used. Additional statements were added in order to put more emphasis on the sharing of online information and privacy, as they seemed to be lacking in Carter and Bélanger’s scale. These statements are: “I have no problems sharing personal information online”, “I believe that the personal
am constantly aware of the possible dangers I am in when using the Internet”. In total, seven statements were used. To measure ‘trust in government’ the existing scale by
Grimmelikhuijsen and Knies (2017) was used, comprised of the three elements of trust they identified: perceived competence, perceived benevolence and perceived integrity. The statements used in this scale were adjusted so they would specifically measure trust in the Dutch government. Eleven statements were used to measure trust in the Dutch government.
Participants were then provided some background information on e-government in the Netherlands, to help them answer the following sets of statements. The next six statements measured perceived usefulness of e-government websites. An existing scale by Carter and Bélanger (2005, p. 24) was slightly adjusted and used to measure this. The next six statements measured perceived ease of use of e-government websites. An existing scale by Carter and Bélanger (2005, p. 24) was also used to measure this after slight adjustments. Finally, intention to use e-government websites was measured using four statements by Carter and Bélanger (2005, p. 24). More information on the items measured by the scales can be found in Appendix A. The survey was created in Dutch and all the existing scales were therefore translated into the Dutch language.
Participants and data cleaning
A sample was created by sharing the survey link on social media and by personally contacting potential participants using Facebook, text messages and e-mail. The people that were approached to take part of the survey were also asked to share the survey within their personal network, to ensure a large amount of responses from a diverse group of participants. Participants had to be over 18 years of age and had to have the Dutch nationality. The total of respondents taking part in the survey was 136 (N = 136).
The data was cleaned to ensure valid analysis. Six participants started the survey but failed to answer any of the questions. These people were deleted from the survey. There were also five people who answered questions regarding demographics (age, education, etc.), but failed to answer any questions relevant to the research question and hypotheses. These people were also deleted from the data. Eight people only partially answered any of the questions relevant to answering the hypotheses. These people were left in the final sample to reduce bias in effect estimates. After cleaning the data, the final sample counted 125 respondents (N = 125). The final sample can be identified by the following characteristics. The sample
consisted of more female than male respondents (64,8%). Respondents were aged between 18 and 79 years old (M = 34,19, SD = 16,31). In general, the respondents had were highly
educated, with almost half of all participants (48%) currently attending university or having a university degree.
For the second item in the scale measuring perceived ease of use of e-government services the values were reversed. The same was done for items 6 and 7 in the scale measuring trust in technology and the fifth question measuring internet use.
Factor analysis and reliability analysis
For each of the different concepts shown in the conceptual model (perceived usefulness of e-government, perceived ease of use of e-government, trust in technology, intention to use e-government and trust in government) a factor- and reliability analysis, including a Varimax rotation, was conducted in order to create a single variable for each of the components that can be used in further analysis. The results of this will be discussed below and illustrated in further detail in Tables 1 through 6. A total overview of the results from the factor and reliability analysis will be found in Table 7 below.
For the first concept, perceived usefulness of e-government, a principal component analysis was conducted. A Kaiser-Meyer-Olkin (KMO) measure of sampling adequacy measured .91, showing that the data was suited for further factor analysis, and Bartlett’s test of sphericity was significant (χ2 (15) = 726.26, p < .001). The component matrix and the Scree plot showed that all six items for the perceived usefulness of e-government loaded onto a single component. The factor showed an Eigenvalue of 4.88 and explained 81.37% of the variance for the entire set of variables. Finally, the communalities were all over .03, which shows that each variable’s variance can be explained by the principal component of perceived usefulness of e-government (see Table 1). An additional reliability analysis showed that the internal consistency of the items is very high (α = .95). The SPSS output also showed that none of the items would lead to a higher Cronbach’s alpha if deleted. Based on these results, all six items were used to create a new variable “USEFULNESS”.
Table 1
Factor loadings and communalities based on the principle component analysis for six items measuring perceived usefulness of e-government services
Item Factor
loading
Communality Item 1 E-government websites allow me to
communicate with government services more efficiently
.90 .8
Item 2 E-government websites allow me to communicate with government services faster
.93 .86
Item 3 E-government websites allow me to
communicate with government services more easily
.91 .83
Item 4 E-government websites provide valuable services to me
.85 .73
Item 5 E-government websites would enhance my effectiveness in searching for and using government services
.89 .79
Item 6 I believe e-government websites are useful .94 .88 Note. The six items from the original survey were translated from Dutch to English
For the second concept, perceived ease of use of e-government, another principal component analysis was conducted. The KMO test measured .86, showing that the data was suited for further factor analysis, and Bartlett’s test was significant (χ2 (15) = 503.1, p < .001). The component matrix and the Scree plot showed that all six items for the perceived ease of use of e-government loaded onto a single component. The factor showed an
Eigenvalue of 4.2 and explained 69.50% of the variance for the entire set of variables. The communalities were all over .03 (see Table 2). An additional reliability analysis showed that the internal consistency of the items was very high (α = .91) and that none of the items would lead to a higher Cronbach’s alpha if deleted. All six items were used to create a new variable “EASEOFUSE”.
Table 2
Factor loadings and communalities based on the principle component analysis for six items measuring ease of use of e-government services
Item Factor
loading
Communality Item 1 Learning to interact with e-government websites
would be easy for me
.88 .77
Item 2 I believe e-government websites are difficult to use .72 .51 Item 3 Interacting with e-government websites is a clear
and easy process
.92 .85
Item 4 I believe e-government websites are easy to use .89 .79 Item 5 I believe it is easy to find the information I am
looking for on e-government websites
.81 .66
Item 6 I believe using e-government websites is useful .77 .59 Note. The six items from the original survey were translated from Dutch to English
For the third concept, trust in technology, another principal component analysis was conducted. A KMO test measured .83, showing that the data was suited for further factor analysis, and Bartlett’s test was significant (χ2 (21) = 327.38, p < .001). The rotated component matrix and the Scree plot showed that the seven items for trust in technology loaded onto two components. The components showed an Eigenvalues of 3.45 (explaining 49,22% of total variance) and 1.17 (explaining 16.75% of total variance) respectively. The communalities were all over .03 (see Table 3). An additional reliability analysis showed a moderate internal consistency of the items (α = .57). Nonetheless, a new variable
“TRUSTINTECH” was computed using all seven items of the scale measuring trust in technology, as the scale was found to be reliable and the Cronbach’s Alpha would not increase much by excluding items.
Table 3
Factor loadings and communalities based on the principle component analysis for seven items measuring trust in technology
Item Factor loading
component 1
Factor loading component 2
Communality Item 1 Today, the internet has
enough safeguards to make me feel comfortable using it
.87 .75
Item 2 I feel assured that legal and technological structures adequately protect me on the internet
.88 .79
Item 3 In general, the internet is now a safe environment
.84 .73
Item 4 I do not have any problems with sharing personal information online
.51 -.46 .47
Item 5 I believe that the personal information I share online is safe
.71 -.31 .59
Item 6 I worry about my privacy when using the internet
-.31 .68 .57
Item 7 I am aware of the possible dangers I am facing when using the internet
.85 .72
Note. Factor loadings < .3 are suppressed; the original seven items from the survey were translated from Dutch to English
A principal component analysis was also conducted for the fourth concept: intention to use e-government services. A KMO test measured .78, showing that the data was suited for further factor analysis, and Bartlett’s test was significant (χ2 (6) = 269.32, p < .001). The component matrix and the Scree plot showed that the seven items measuring intention to use e-government services loaded onto a single component. The Eigenvalue for this component was 2.96 and explained 74.04% of the total variance. Again, the communalities were all over .03 (see Table 4). An additional reliability analysis showed a high internal consistency of the items (α = .88). Because of these results, the variable “INTENTION” was created using all four items from the scale.
Table 4
Factor loadings and communalities based on the principle component analysis for four items measuring intention to use e-government services
Item Factor
loading
Communality Item 1 I would use e-government websites for gathering
information
.82 .66
Item 2 Interacting with government services using e-government websites is something I would do
.89 .79
Item 3 I would not hesitate to provide personal information to e-government websites
.82 .68
Item 4 I plan on using e-government websites to take care of government-related business
.91 .83
Note. The original four items from the survey were translated from Dutch to English Another principal component analysis was conducted for the concept trust in government. The KMO test measured .94 and Bartlett’s test was significant (χ2 (55) = 1477.69, p < .001). The component matrix and the Scree plot showed that the eleven items measuring trust in government loaded onto a single component. The Eigenvalue for this component was 8.16 and explained 74.15% of the total variance. Again, the communalities were all over .03 (see Table 5). An additional reliability analysis showed a high internal consistency of the items (α = .97). Because of these results, the variable “TRUSTINGOV” was created using all eleven items from the scale.
Table 5
Factor loadings and communalities based on the principle component analysis for eleven items measuring trust in government
Item Factor
loading
Communality Item 1 Overall, the Dutch government does a good job
fulfilling its duties
.84 .71
Item 2 The Dutch government is competent and effective .87 .75 Item 3 The Dutch government carries out its duty very
well
.89 .79
Item 4 The Dutch government is knowledgeable .88 .78 Item 5 If citizens need help, the Dutch government will do
its best to help them
.85 .72
Item 6 The Dutch government acts in the interest of citizens
.88 .77
Item 7 I believe the Dutch government is genuinely interested in the well-being of citizens
.84 .70
Item 8 I believe the Dutch government approaches its citizens in a sincere way
.86 .74
Item 9 I would characterize the Dutch government as sincere
.90 .80
Item 10 I believe the Dutch government would keep its commitments
.81 .65
Item 11 I would characterize the Dutch government as honest
.86 .74
Note. The original eleven items from the survey were translated from Dutch to English Finally, an additional principal component analysis was conducted in order to create a single variable measuring the moderating variable internet use. After consideration the second and third question measuring internet use in the online survey (asking how participants spend their time on the internet i.e. for work or for pleasure) were not used for analysis, in order to create a scale measuring participants’ time spent online more generally. The KMO test measured .75 and Barlett’s test was significant (χ2 (3) = 211.79, p < .001). The component matrix and the Scree plot showed that the three items measuring Internet use loaded onto a single component. The Eigenvalue for this component was 2.46 and explained 82.11% of the total variance. The communalities were all over .03 (see Table 6). Reliability analysis showed a high internal consistency of the items (α = .89). The variable “INTERNETUSE” was
Table 6
Factor loadings and communalities based on the principle component analysis for three items measuring Internet use
Item Factor loading Communality
Item 1 How often do you use the internet? .90 .81
Item 2 I use the internet often .91 .83
Item 3 I do not spend a lot of time on the internet .91 .83 Note. The original three items from the survey were translated from Dutch to English Table 7
Factor and reliability analysis for all scales
Variable Components Eigenvalue Total variance explained (%) Cronbach’s Alpha Perceived usefulness 1 4.88 81.37 .95 Perceived ease of use 1 4.17 69.50 .91 Trust in technology 2 3.45 49.22 .57 1.17 16.75 Intention to use 1 2.96 74.04 .88 Trust in government 1 8.16 74.15 .97 Internet use 1 2.46 82.11 .89
Plan for analysis
To answer the first three hypotheses measuring the relationship between independent variables perceived usefulness of government websites, perceived ease of use of
e-government websites and trust in technology to intention to use of e-e-government websites, three linear regression analyses will be conducted. Another linear regression will be
conducted to answer the fourth hypothesis measuring the relationship between intention to use e-government websites and trust in government. The fifth, sixth and seventh hypotheses (the mediation hypotheses) will be measured using Baron and Kenny’s (1986) four-step approach. The results from the previous regression analyses will be checked for statistical significance, in addition to the results from three linear regression analyses measuring the relationships between perceived usefulness, perceived ease of use, trust in technology and trust in
government. Finally, three linear regression analyses will be conducted with both one of the original independent variables and intention to use e-government websites as independent
variables and trust in government as dependent variables. The results from the last three analyses will reveal if mediation takes place. A Sobel Test is used to see if this mediation is statistically significant. An online calculator is used to calculate Sobel’s Z.
Before the seven hypotheses could be checked, the significance of all regression models were checked using an F-test. All regressions were statistically significant. Because of this significance, the assumptions for all analyses were checked. First, a series of scatterplots were created to check for linearity between the independent variables and the dependent variable. Additionally, histograms and P-P plots showed that the residuals were
approximately normally distributed. Scatterplots using the standardized predicted value and standardized residual value also showed that homoscedasticity was present for all regression analyses. There was also no multicollinearity between the variables, as all VIF values were low. Finally, the values for all Durbin Watson tests were between 1.5 and 2.5, meaning that there is no autocorrelation.
Results
In order to answer the research question (How does Dutch citizens’ evaluation of the switch from ‘paper’ government communication to e-government communication influence their (intention to) use e-government services and how does this influence citizens’ trust in government?) several regression analyses were ran using SPSS in order to test all hypotheses. The results from these analyses will be discussed below.
Correlations
In order to prepare for the regression analyses a correlation matrix was created to see if there was any correlation (either positive or negative) between different all the different variables needed to answer the hypotheses. The five variables needed to answer our research question and main hypotheses (perceived usefulness of e-government websites, perceived ease of use of e-government websites, trust in technology, intention to use e-government websites and trust in government) were all significant and positively correlated with each other. A few control variables, internet use, age, education, and gender, were also included in the correlation matrix. Internet use was found to be significant and positively correlated with all other variables. As predicted, age is the only variable that is negatively correlated with all other variables. Gender was found to not be significantly correlated with any of the variables,
and will therefore not be included in any further analysis. Furthermore, age (r = -.14, p = .123) and education (r = .13, p = .149) were non-significantly correlated with trust in technology. All correlations can be found in Table 8.
Table 8 Correlation matrix Variable 1 2 3 4 5 6 7 8 9 Mean SD 1 Perceived usefulness Pearson Correlation 1 5.07 1.22 Significance 2 Perceived ease of use Pearson Correlation .76 1 4.81 1.24 Significance <.001 3 Trust in technology Pearson Correlation .31 .27 1 3.67 .77 Significance .001 .003 4 Intention to use Pearson Correlation .81 .66 .48 1 4.83 1.27 Significance <.001 <.001 <.001 5 Trust in government Pearson Correlation .48 .35 .3 .30 1 4.20 1.26 Significance <.001 <.001 .001 .001 6 Internet use Pearson
Correlation .53 .48 .2 .2 .23 1 6.14 1.32 Significance <.001 <.001 .03 <.001 .011 7 Age Pearson Correlation -.54 -.39 -.14 -.56 -.39 -.61 1 34.19 16.31 Significance <.001 <.001 .123 <.001 <.001 <.001 8 Education Pearson Correlation .55 .37 .13 .54 .28 .61 -.54 1 5.9 1.42 Significance <.001 <.001 .149 <.001 .002 <.001 <.001 9 Gender Pearson Correlation .2 .11 .07 .17 .17 .01 -.22 .01 1 1.65 .48 Significance .032 .259 .423 .073 .052 .755 .014 <.001 Hypothesis testing
A linear regression analysis was conducted to check the first hypothesis. In this analysis intention to use was used as the dependent variable and perceived usefulness as the independent variable. Age, education and internet use were added as control variables. The regression analysis shows that the relationship between perceived usefulness and intention to use is significant and that the strength of this positive relationship is quite strong (β = .67, t = 9.74, p < .001). Furthermore, the analysis shows that 68.7% of variance in intention to use e-government websites could be explained by perceived usefulness of e-e-government websites (R2 = .69), when controlling for the descriptive variables. Based on these results, the first hypothesis can be accepted. This means that when e-government websites are perceived as useful, people are more likely to use them.
A linear regression analysis was also conducted to check the second hypothesis. The regression analysis shows that the relationship between perceived ease of use and intention to use is significant and that the strength of this positive relationship is quite strong (β = .47, t = 6.62, p < .001). Additionally, the analysis shows that 58.4% of variance in intention to use e-government websites could be explained by perceived usefulness of e-e-government websites (R2 = .58). Hypothesis 2 can also be accepted. The easier to use e-government websites appear, the more willing people are to use them.
A third linear regressions analysis was conducted to check the third hypothesis. The regression analysis shows that the relationship between trust in technology and intention to use is significant but that the strength of this positive relationship is only moderately strong (β = .4, t = 6.28, p < .001). Additionally, the analysis shows that 57.2% of variance in intention to use e-government websites could be explained by trust in technology (R2 = .57). The results show that hypothesis 3 can also be accepted. The more people trust technology and the more comfortable people feel using the internet, the more willing they are to use
e-government websites.
Another linear regression analysis was conducted to check the fourth hypothesis. In this analysis trust is government was used as the dependent variable and intention to use as the independent variable. Age, education and internet use were added as control variables. The regression analysis shows that the relationship between intention to use and trust in government is significant and that the strength of this positive relationship is moderately (β = .59, t = 5.87, p < .001). Furthermore, the analysis shows that 34.6% of variance in intention to use e-government websites could be explained by perceived usefulness of e-government websites (R2 = .35), when controlling for the descriptive variables. Based on these results, the fourth hypothesis can be accepted. This means that when people want to use e-government websites, they are also more trusting of government in general.
To test the mediation effect of intention to use of e-government websites on the relationship between perceived usefulness of e-government websites and trust in government Baron and Kenny’s four-step approach to mediation was used (Baron & Kenny 1986). Previous analyses for the first and fourth hypothesis showed that both there were positive significant relationships between perceived usefulness and intention to use and between intention to use and trust in government. An additional linear regression was conducted to see if there was a significant relationship between perceived usefulness and trust in government,
controlling for age, education and internet use, and thus if mediating is able to occur. The SPSS results show that there is a moderate, positive and statistically significant relationship between perceived usefulness and trust in government (B = .47, β = .45, t = 4.31, p <.001). Due to the fact that the first three steps for Baron and Kenny’s mediation analysis were significant, a final multiple linear regression analysis was conducted using both perceived usefulness and intention to use as independent variables and trust in government as dependent variable. Perceived usefulness was no longer statistically significant (t = .59, p = .56), while intention to use remained statistically significant (t = 3.9, p < .001). These findings support a full mediation between perceived usefulness of e-government websites, intention to use them and trust in government. A Sobel test confirms the statistical significance of the mediation effect (Z = 9.86, p < .001).
Baron and Kenny’s approach to mediation analysis was also used to test the mediation effect of intention to use e-government websites on the relationship between perceived ease of use of e-government websites and trust in government. Previous analyses for the second and fourth hypothesis showed that there were positive significant relationships between perceived ease of use and intention to use and between intention to use and trust in government. An additional linear regression was conducted to see if there was a significant relationship between perceived ease of use and trust in government, controlling for age, education and internet use, and thus if mediation is able to occur. The SPSS results show that there is a weak but positive and statistically significant relationship between perceived ease of use and trust in government (B = .29, β = .28, t = 2.93, p = .004). Due to the fact that the first three steps for Baron and Kenny’s mediation analysis were significant, a final multiple linear regression analysis was conducted using both perceived ease of use and intention to use as independent variables and trust in government as dependent variable. Perceived ease of use was no longer statistically significant (t = .04, p = .97), while intention to use remained statistically
significant (t = 4.93, p < .001). These findings support a full mediation between perceived ease of use of e-government websites, intention to use them and trust in government. Sobel’s test confirmed the statistical significance of the mediation effect (Z = 4.4, p < .001).
Baron and Kenny’s approach to mediation analysis was also used a final time to test the mediation effect of intention to use e-government websites on the relationship between trust in technology and trust in government. Previous analyses for the third and fourth hypothesis showed that there were positive significant relationships between trust in
technology and intention to use and between intention to use and trust in government. An additional linear regression was conducted to see if there was a significant relationship between trust in technology and trust in government, controlling for age, education and internet use, and thus if mediation is able to occur. There appeared to be a weak but positive and statistically significant relationship between perceived ease of use and trust in
government (B = .43, β = .26, t = 3.18, p = .002). Due to the fact that the first three steps for Baron and Kenny’s mediation analysis were significant, a final multiple linear regression analysis was conducted using both trust in technology and intention to use as independent variables and trust in government as dependent variable. Trust in technology was no longer statistically significant (t = .36, p = .72), while intention to use remained statistically significant (t = 4.84, p < .001). These findings support a full mediation between trust in technology, intention to use e-government websites and trust in government. Sobel’s test confirmed the statistical significance of the mediation effect (Z = 4.29, p < .001).
Additional analysis
While all seven hypotheses were based on findings from previous literature, just like the fourth hypothesis suggesting a positive effect from intention to use e-government services to trust in government, there were also some studies that found evidence for a positive effect from trust in government to (intention to) use. For example, Carter and Bélanger (2005) concluded that higher levels of trust in state government agencies will be positively related to higher levels of intention to use a state e-government service. They write: “ […] citizens who perceive the agencies to be more trustworthy will be more likely to adopt e-government services. Components of trustworthiness identified in previous work on e-commerce, such as benevolence, integrity and competence, could be considered as starting points for state governments to act on (p. 19).” Welch, Hinnant, and Moon (2004) speak of a reciprocal relationship between e-government satisfaction and trust in government. They conclude:
Results show that those individuals who are more satisfied with e-government and government Web sites also trust the government more and those individuals who trust government more are also more likely to be satisfied with e-government.
Although we cannot speak directly to the causality of this relationship, the finding of association is important and indicates the fundamental embeddedness of electronic government in social institutions and norms, even at this early stage in the
While Welch, Hinnant, and Jae Moon look at e-government satisfaction and not intention to use e-government, it seems logical that the same conclusion could be drawn for intention to use e-government websites. Additionally, Horsburgh, Goldfinch, and Fauld (2011) base their study on findings from other studies that state that higher levels of trust in government correlate with more intensive e-government services use and that those satisfied with such services are more trusting of government.
Due to these findings, an additional linear regression analysis was conducted with trust in technology as the independent variable and intention to use e-government websites as the dependent variable. Again, age, education and internet use were added as control variables. The F-test of this analysis showed that the regression model was statistically significant (F(4, 111) = 34.9, p < .001). Next, the assumptions for this analysis were checked. Scatterplots were created to show linearity and homoscedasticity and a histogram and P-P plot were created to measure normality of residuals. The Durbin Watson test value was 2.1 (Durbin Watson = 2.1). The linear regression analysis continued and showed that there was a moderate, positive relationship between trust in government and intention to use
e-government websites (B = .4, β = .4, t = 5.87, p < .001). These results and the results from the analysis for the fourth hypothesis show that there is a positive relationship between intention to use e-government and trust in government, as well as a positive relationship between trust in government and intention to use e-government. This indicates that there is a reciprocal relationship between intention to use and trust in government. Those who intend to use e-government are not only more trusting of e-government, but those who trust e-government more are also more likely to intend to use e-government websites.
Table 9
Regression results and hypothesis testing
Relation B SE Beta t p 95% Confidence
Interval
Support H1 PU x ITU .7 .07 .67 9.74 <.001 [.56, .85] Yes H2 PEAU x ITU .48 .07 .47 6.62 <.001 [.34, .62] Yes H3 TIT x ITU .66 .11 .4 6.28 <.001 [.45, .87] Yes H4 ITU x TIG .59 .1 .59 5.87 <.001 [.39, .79] Yes H5 PU x TIG .47 .11 .45 4.31 <.001 [.69, .59] Yes
PU x ITU x TIG .09 .14 .08 .59 .56 [-.2, .37] .54 .14 .54 3.9 <.001 [.26, .81]
H6 PEOU x TIG .29 .1 .28 2.93 .004 [.1, .49] Yes PEOU x ITU x
TIG
.004 .11 .004 .04 .97 [-.21, .22] .59 .12 .59 4.93 <.001 [.35, .83]
H7 TIT x TIG .43 .13 .26 3.18 .002 [.16, .69] Yes TIT x ITU x TIG .06 .15 .03 .36 .72 [-.25, .36]
.57 .12 .57 4.84 <.001 [.34, .81]
+ TIG x ITU .4 .07 .4 5.87 <.001 [.26, .53] Yes Note. The abbreviations mean the following: PU (perceived usefulness), PEAU (perceived ease of use), TIT (trust in technology), ITU (intention to use), TIG (trust in government). All the regression results were controlled for by age, education and internet use.
Discussion and conclusion
This study aimed to find out how the change in the way the Dutch government communicates to its public, by implementing the use of ICTs, changes people’s trust in their government. As literature points out, digitization can make communication go faster, more effectively and smoother. While this sounds nice in theory, reports on the progress of the Digitaal 2017 program created by the Dutch government revealed that in practice digitization of government is not always perceived as well as one would expect. This problem led to the following research question: How does Dutch citizens’ evaluation of the switch from ‘paper’ government communication to e-government communication influence their intention to use e-government websites and how does this influence citizens’ trust in government?
Findings
Interpreting the results, it can be concluded that all seven hypotheses (plus an extra analysis looking at the way trust in government influenced intention to use of e-government websites) were accepted. The first three hypotheses were based on computed mediated
communication theories (CMC). The first two were based on Davis’ (1989) Technology Acceptance Model, which explains that perceived usefulness and perceived ease of use of a technological device or program influences people intention to use technology. The third hypothesis was based on literature (Ranaweera, 2016; Gilbert, Balestrini, & Littleboy, 2004; Carter & Bélanger, 2005) which found that trust in technology is also linked to intention to use technology. After interpreting the results from the survey, it was found that all three of these variables had a moderately strong, positive effect on intention to use e-government websites. These results show that the more people view e-government as a useful
development, the more likely they are to actually use it. The easier the e-government websites are to navigate, the more likely people are to use them as well. Finally, the more secure people feel online and the less they worry about possible online dangers like fraud, privacy issues or security issues, the more likely they are to use e-government websites. Out of these three independent variables perceived usefulness of e-government websites had the strongest effect.
The fourth hypothesis was based on another CMC theory. Walther and Burgoon’s (1992) Social Information Processing Theory explained how online interactions can have similar emotional impacts to offline interactions, and thus can explain how people’s intention to use e-government websites can lead to more trust in government. This claim was supported by several previous studies (e.g. Tolbert & Mossberger, 2006; Welch, Hinnant, & Jae Moon, 2004). This study of people’s intention to use e-government websites and trust in government in the Netherlands found similar results. A moderate, positive effect was found between intention to use and trust in government. However, due to some literature (e.g. Welch,
Hinnant, & Jae Moon, 2004; Carter & Bélanger, 2005; Horsburgh, Goldfinch, & Fauld, 2011) pointing at an opposite effect, an extra analysis was performed. This analysis revealed that there was also a positive effect from trust in government to intention to use e-government websites, indicating a reciprocal relationship. The effect that trust in government had on intention to use, however, was not as strong as the effect from intention to use to trust in government. The final three hypotheses measuring the mediating effect that intention to use e-government websites has between the three independent variables on trust in e-government. For all three hypotheses a full mediation was found.
Academic and practical implications
These significant findings have several practical and academic implications. First, the findings of this study are believed to contribute to the current discussion on e-government and the implementation of ICTs in different types of organizations. While previous literature indicates that perceived usefulness of government websites, perceived ease of use of government websites and trust in technology influences people’s intention to use
e-government and also that people’s intention to use e-e-government has a positive effect on their overall trust in government, this study adds an interesting new perspective on this existing literature by showing that intention to use functions as a mediator between perceived
usefulness, perceived ease of use, trust in technology and trust in government. This study also adds to existing literature by confirming a reciprocal relationship between intention to use e-government websites and trust in e-government.
Besides academic implications this study also has several practical implications. First, as a significant relationship was found between intention to use e-government and trust in government, government organizations should focus on what factors give people the intention to use their websites. As trust in government is believed to be strongly related to effectiveness of government, making people want to use their websites is highly important for government organizations. As the findings of this study show, perceived usefulness, perceived ease of use and trust in technology all have a positive effect on people’s intention to use e-government, and it should thus be of high priority for government organizations to improve these factors. Government organizations could improve perceived usefulness of their websites by educating people on the benefits of online communication by for example creating television
commercials telling people that they can communicate with government cheaper, faster, and easier if they use e-government websites. Government organizations should also give their websites simpler and more minimalistic designs in order to make their websites easier to use. Today, government websites in the Netherlands are often perceived as complicated to use, as becomes clear when reading the 2017 ombudsman report (Verhoef et al.) Furthermore, government organizations should invest more in online security systems as this will hopefully make people feel less worried for their online safety when using e-government websites and thus increasing their intention to use them.
Limitations and suggestions for future research
This study also has some points for improvements Since participants for the final sample were collected by contacting the researcher’s personal network and those people were the only people who spread the survey, the sample might not represent the whole populations as most participants were from the same social milieu. For example, almost half of all
participants were highly educated and had a university education. This study also did not differentiate between different types of e-government, but studies the concept as a whole. Future studies could make a differentiation between different types of e-government websites as people might have different opinions of different websites. Additionally, as the results from the regression analyses revealed that some of the predictor variables appeared to only explain a small part of the variance for intention to use e-government website, future studies might try to find additional explanations for intention to use e-government.
In conclusion, this study discovered how government services could best deal with the changing communication environment and the implementation of e-government. By using the knowledge that intention to use e-government websites improves people’s trust in
government, these services could look at the variables that improves peoples’ intention to use and thus improve overall trust in their organizations. These findings will hopefully inspire government services to implement e-government services in such a way that it is not only beneficial for their own organizations, but it also makes interaction with government easier, faster, smoother, and safer for citizens.
Acknowledgements
I would like to express my gratitude to my thesis supervisor Dr. P. Verhoeven of the University of Amsterdam for continuously taking time out of his busy schedule to provide me with his feedback and helpful suggestions. Additionally, I would like to thank all other
professors and staff members at the Graduate School of Communication and everyone who took the time to fill out and/or share my survey.
References
Ahn, M.J., & Bretschneider, S. (2011). Politics of E-Government: E-Government and the Political Control of Bureaucracy. Public Administration Review, 71(3), 414-424. Baron, R.M., & Kenny, D.A. (1986). The Moderator-Mediator Variable Distinction in Social
Psychological Research: Conceptual, Strategic, and Statistical Considerations. Journal of Personality and Social Psychology, 51(6), 1173-1182.
Carter, L. & Bélanger, F. (2005). The utilization of e-government services: citizen trust, innovation and acceptance factors. Information Systems Journal, 15(1), 5-25. Cascio, W.F., & Montealegre, R. (2016). How Technology is Changing Work and
Organizations. Annual Review of Organizational Psychology and Organizational Behavior, 3, 349-375.
Chun, S.A. et al. (2010). Government 2.0: Making connections between citizens, data and government. Information Polity, 15, 1-9.
Davis, F.D. (1989). Perceived Usefulness, Perceived Ease of Use, and User Acceptance of Information Technology. MIS Quarterly, 13(3), 319-340.
DeLone, W.H., & McLean, E.R. (2003). The DeLone and McLean Model of Information Systems Success: A Ten-Year Update. Journal of Management Information Systems, 19(4), 9-30.
Digitaal 2017: Waar staan we nu? [Digital 2017: Where are we now?]. (2017, February 9). Retrieved from https://www.digitaleoverheid.nl/nieuws/digitaal-2017-waar-staan-we-nu/
Dunleavy, P. (2009). Governance and state organization in the digital era. The Oxford
Handbook of Information and Communication Technologies: Oxford University Press. Gilbert, D., Balestrini, P., & Littleboy, D. (2004). Barriers and benefits in the adoption of
e-government. International Journal of Public Sector Management, 17(4), 286-301. Grimmelikhuijsen, S., & Knies, E. (2015). Validating a scale for citizen trust in government
organizations. International Review of Administrative Sciences, 83(3), 583-601. Guerrier, C. (2016). Security and Privacy in the Digital Era. London: Wiley-ISTE.
Horsburgh, S., Goldfinch, S., & Gauld, R. (2011). Is Public Trust in Government Associated With Trust in E-Government? Social Science Computer Review, 29(2), 232-241. Janowski, T. (2015). Digital government evolution: From transformation to contextualization.
Government Information Quarterly, 32(3), 221-236.
Janssen, M., Charalabidis, Y., & Zuiderwijk, A. (2012). Benefits, Adoption Barriers and Myths of Open Data and Open Government. Information Systems Management, 29(4), 258-268.
Luna-Reyes, L.F., & Gil-Garcia, J.R. (2014). Digital government transformation and internet portals: The co-evolution of technology, organizations, and institutions. Government Information Quarterly, 31(4), 545-555.
Nieminen, H. (2016). Digital divide and beyond: What do we know of Information and Communications Technology’s long-term social effects? Some uncomfortable questions. European Journal of Communication, 31(1), 19-32.
Parent, M., Vandebeek, C.A., & Gemino, A.C. (2005). Building Citizen Trust Through E-government. Government Information Quarterly, 22(4), 720-736.
Plasterk, R.H.A. (2013). Visiebrief digitale overheid 2017. Letter to the Chairman of the House of Representatives.
Prins, J.E.J., Broeders, D., & Griffioen, H.M. (2012). iGovernment: A new perspective on the future of government digitization. Computer Law & Security Review, 28, 273-282. Ranaweera, H.M.B.P. (2016). Perspective of trust towards e-government initiatives in Sri
Lanka. SpringerPlus, 5(22), 1-11.
Rice, R. E. (2017). Flexwork, boundaries, and work-family conflicts: How ICTs and work engagement influence their relationship. In G. Hertel, D. Stone, R. D. Johnson, & J. Passmore (Ed.), Handbook of the psychology of the Internet at work (in press). London, UK: Wiley Blackwell Industrial & Organizational Psychology Series.
Tolbert, C., & Mossberger, K. (2006). The effects of e-government on trust and confidence in government. Public Administration Review, 66(3), 354-369.
Van Kooten, T., & Weller, M. (2006). E-Government in Nederland. Statistische meting van elektronische overheidsdiensten: inventarisatie van openbare bronnen en enige analyse. Centraal Bureau voor de Statistiek.
Verhoef, J. et al. (2017). “Hoezo MIJNoverheid?”: Onderzoek naar knelpunten voor burgers bij MijnOverheid / de Berichtenbox. Retrieved from
https://www.nationaleombudsman.nl/system/files/onderzoek/DEF%20Rapport%20Ho ezo%20MijnOverheid.pdf
VVD, CDA, D66 and ChristenUnie. (2017) Vertrouwen in de toekomst. Retrieved from https://www.tweedekamer.nl/sites/default/files/atoms/files/regeerakkoord20172021.pd f
Walther, J.B., & Burgoon, J.K. (1992) Relational Communication in Computer-Mediated Interaction. Human Communication Research, 19(1), 50-88.
Walther, J.B. (2011). Theories of Computer-Mediated Communication and Interpersonal Relations. In Knapp, M.L. & Daly, J.A. (Eds.), The Handbook of Interpersonal Communication (443-479). Thoasand Oaks, CA: Sage.
Welch, E., Hinnant, C., & Jae Moon, M. (2004). Linking citizen satisfaction with
e-government and trust in e-government. Journal of Public Administration Research and Theory, 15(3), 371-391.
Appendix: Survey
Geachte deelnemer,
Hierbij wil ik u uitnodigen om deel te nemen aan een onderzoek dat deel uitmaakt van mijn Master's thesis in Corporate Communication. Het onderzoek zal worden uitgevoerd onder de auspiciën van de Graduate School of Communication, een onderdeel van de Universiteit van Amsterdam.
De naam van het onderzoek waarvoor ik uw medewerking vraag is 'E-government'. Er wordt u gevraagd een aantal vragen te beantwoorden en op een aantal stellingen te reageren. Het doel van het onderzoek is kijken wat de beweegredenen zijn voor mensen om
overheidswebsites te bezoeken en of dit in verband staat met vertrouwen in overheidsinstanties.
Deelname aan het onderzoek kost ongeveer 5-10 minuten. De vragen zijn het beste zichtbaar op uw desktop, laptop of tablet. Als u gebruikt maakt van een smartphone wordt het
geadviseerd uw scherm te draaien.
Aangezien dit onderzoek wordt uitgevoerd onder de verantwoordelijkheid van de ASCoR, Universiteit van Amsterdam, wordt u gegarandeerd dat:
1) Uw anonimiteit wordt gewaarborgd en uw persoonlijke gegevens worden niet doorgegeven, tenzij u daarvoor nadrukkelijk toestemming geeft.
2) U kunt weigeren deel te nemen aan het onderzoek of uw deelname inkorten zonder dat u een reden hoeft op te geven. U heeft ook 24 uur na deelname om uw toestemming terug te trekken om uw antwoorden of gegevens te gebruiken in het onderzoek.
3) Deelname aan het onderzoek houdt niet in dat u aan een merkbaar risico of ongemak wordt blootgesteld en u zult niet worden blootgesteld aan expliciet aanstootgevend materiaal. 4) Uiterlijk vijf maanden na afsluiting van het onderzoek kan u een onderzoeksrapport worden aangeboden dat de algemene resultaten van het onderzoek worden toegelicht. Voor meer informatie over het onderzoek en de uitnodiging om deel te nemen, bent u van harte welkom om contact op te nemen met projectleider Kim Baeten via
kimbaeten@hotmail.com
Als u klachten of opmerkingen heeft over het verloop van het onderzoek en de procedures kunt u contact opnemen met de aangewezen lid van de ethische commissie die ASCoR vertegenwoordigt. Klachten of opmerkingen worden strikt vertrouwelijk behandeld. Het ASCoR secretariaat is beschikbaar op het volgende adres:
ASCoR secretariaat, ethische commissie Universiteit van Amsterdam
Postbus 15793, 1001 NG, Amsterdam 020-5253680
