a model based on theory of planned behaviour (tbp) - CiteSeerX

European and Mediterranean Conference on Information Systems 2009 (EMCIS2009) July 13-14 2009, Crowne Plaza Hotel, Izmir

EXPLAINING CITIZEN ADOPTION OF GOVERNMENT TO CITIZEN SERVICES: A MODEL BASED ON THEORY OF PLANNED BEHAVIOUR (TBP) İrfan Emrah Kanat, Information Systems (IS) Informatics Institute, Middle East Technical University, TR [email protected] Sevgi Özkan, Information Systems (IS) Informatics Institute, Middle East Technical University, TR [email protected]

Abstract E-government initiatives are gaining traction worldwide, Unfortunately not all e-government initiatives end up being successful. The main determinant of failure for government to Citizen services is the low adoption by citizens. A better understanding of the factors influencing citizens' adoption behavior is required to guide e-government implementations. E-government adoption models can provide such an insight. The aim of this study is to develop a model that encompasses various dimensions of e-government that relate to citizen adoption behavior while still providing the mechanisms that can account for differences among different countries and implementations. Keywords: e-government, adoption, citizen adoption, theory of planned behavior, government to citizen services, trust, ease of use, usefulness, access, skills

1

INTRODUCTION

E-Government is the use of information technology in government services. The differences in governmental activities manifest themselves in distinct types of e-government services they produce. It is obvious that an internal database for the back office automation would be vastly different from a service provided directly to the citizens over the web. There are various categorization schemes in the literature but United Nations (UN) uses a simple categorization. The services are grouped according to the parties involved as; Government to Government (G2G), Government to Business (G2B) and Government to Citizen (G2C) which also happens to be the focus of this study (DESA, 2008). As noted by Carter and Bélanger (2005), e-government has increased the efficiency with which the governmental services are provided. The increased benefits attracted governments worldwide so that, among all 192 countries surveyed in DESA (2008) there was not a single country without an egovernment implementation. Unfortunately, not all of these implementations which consumed considerable amount of resources were successful. Studies conducted in Manchester University, UK revealed that only 15% of the e-government initiatives managed to completely fulfil their goals (Heeks, 2008). According to DESA (2008), the possible reasons behind the failure of e-government projects include infrastructural issues, accessibility, usefulness, social and cultural issues, lack of understanding of citizen needs, lack of trust, lack of marketing, and/or lack of confidentiality. This finding is in line with the previous work in e-government adoption literature which has already highlighted these reasons under such titles as; digital divide or ICT divide (Oxendine, Borgida, Sullivan & Jackson, 2003; Carter & Weerakkody, 2008), social and cultural issues (Carter & Weerakkody, 2008), trust and Kanat, İrfan Emrah and Özkan, Sevgi Explaining Citizen Adoption Of Government to Citizen Services: A Model Based on Theory of Planned behaviour (TBP)

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risk (Belanger & Carter, 2008; Gefen, Warkentin, Pavlou & Rose, 2002), perceived usefulness and perceived ease of use (Gefen et al., 2002; Carter & Bélanger, 2005) as factors influencing adoption. The aim of this study is to develop a model that can be used for the prediction and explanation of citizen behaviour regarding the acceptance of a G2C e-government service. Considering the wide range of applications of e-government services, such a model should account for infrastructural and cultural differences among countries, the results of differing technologies employed, and the perceptions of governments that implement these services while not loosing it's theoretical support. A measurement instrument to empirically test and validate this model will also be developed alongside the model.

2

LITERATURE REVIEW

2.1

E-Government Adoption Models

Adoption models in e-government have been closely following such models in e-commerce. The similarities between e-government and e-commerce had been reported before even claimed, egovernment in G2C settings are analogous to e-commerce (Carter & Bélanger, 2005; Conklin, 2007). The models developed so far in both lines of research usually combined a technology adoption model with constructs from various other domains that were deemed relevant. Carter and Bélanger (2005) define the model they developed as a combination of constructs from information systems, sociology and public administration. Diffusion of Innovations theory, TAM and some constructs from previous Trustworthiness studies were combined to form the model they developed. Carter & Weerakkody (2008) combined Technology Acceptance Model with Trust and ICT divide constructs to conduct an inter-cultural comparison among US and UK. Gefen et al. (2002) integrated social influence, trust and risk constructs on top of TAM. (AlAwadhi & Morris, 2008) validated the UTAUT model in the context of a developing country. (Hung et al., 2006) in an approach not so different from this study embraced TPB and enriched the model with many constructs from various models of technology adoption. Study

Base model

Additional constructs

Carter and Belanger (2005)

Diffusion of Innovations

Perceived Usefulness, Perceived Ease of Use, Trust

Carter and Weerakkody (2008)

TAM

Trust, Skills and Access

Gefen et al. (2002)

TAM

Social influence, Trust and Risk

(AlAwadhi & Morris, UTAUT 2008) (Hung et al., 2006)

Decomposed TPB

Perceived Usefulness, Perceived Ease of Use, Perceived Risk, Trust, Personal Innovativeness, Compatibility, External Influence, Interpersonal Influence, Self Efficacy, Facilitating Conditions

Table 1: Previous e-government adoption models One major pitfall that can be observed in most of these studies is the theoretical inconsistencies. By arbitrarily combining various constructs of different models from diverse domains, the internal consistency of constructs are being flawed. Sometimes the constructs included are so similar that they overload or mediate each other out. Another related issue as pointed out by Ajzen (2002c) is the use of invalidated or incompatible survey items. Consequently, a theoretically sound model with good Kanat, İrfan Emrah and Özkan, Sevgi Explaining Citizen Adoption Of Government to Citizen Services: A Model Based on Theory of Planned behaviour (TBP)

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empirical support, which includes facilities for further expansion, would still be a valuable addition to the literature. 2.2

Base Models

There are various models that can be used as a base for developing a citizen adoption model but since the main enabler of e-government is technology, the base models usually come from technology adoption studies. Among these models, Technology Acceptance Model (TAM) is the most prominent example. Davis's seminal work, TAM is widely known in the IS literature and has the widest acceptance (Benbasat & Barki, 2007). TAM was built on a psychology theory, Ajzen and Fishbein’s (1972) Theory of Reasoned Action (TRA) which was used to explain human behaviour. Davis (1989) took TRA, simplified the model by removing the extras and arrived at a simple model that produced consistent results. According to Davis (1989) IT adoption behaviour depends on two basic constructs: Perceived Usefulness (PU) and Perceived Ease of Use (PEOU). Perceived usefulness is the perception of additional performance gained by the use of the system in question. Perceived ease of use is the perceived reduction in effort required to carry out the task by using the system in question. Perceived usefulness and Perceived Ease of Use combined, determine the Intention to Use the System which in turn has an effect on the Actual System Use. (Davis, 1989) found that Perceived Ease of Use was also an antecedent of Perceived Usefulness and was partially mediated over the later. Over the years since its conception in 1986 it has been validated over and over again to a point of almost certainty.

Figure 1: Technology Acceptance Model Other models such as Uniform Theory of Acceptance and Use of Technology (UTAUT) (Venkatesh, Morris, Davis & Davis, 2003) and Diffusion of Innovations (DOI) (Moore & Benbasat, 1991) also exist. These models have introduced additional constructs on top of TAM, to explain technology acceptance but a general evaluation of each model reveals that, similar constructs can be observed in each model, under different names. Usability (perceived ease of use of TAM, technical complexity of DOI, effort expectancy of UTAUT) and functionality (perceived usefulness of TAM, relative advantage of DOI, performance expectancy of UTAUT) consistently showed strong effects on intention to use and actual use in the broadest set of contexts. Yet TAM's limitations on the basis of extensibility and explanation power have been noted (Benbasat & Barki, 2007). According to Benbasat and Barki, TAM while providing a simple and effective tool for explaining IT adoption, failed to provide mechanisms for inclusion of other constructs. That was because those mechanisms were removed from the model in the transition from TRA to TAM for the sake of simplicity. UTAUT returned social norms of TRA and the perceived behaviour al control of Theory of Planned Behaviour (TPB) but failed to return extension facilities. As Benbasat & Barki (2007) pointed out, extending TAM or UTAUT required the researchers to justify the additional constructs in terms of the model used, extending these models without surpassing their theoretical boundaries was difficult. Another point made against the use of these models by Benbasat and Barki was the explanatory power of these models. TAM did not mean all that much to Kanat, İrfan Emrah and Özkan, Sevgi Explaining Citizen Adoption Of Government to Citizen Services: A Model Based on Theory of Planned behaviour (TBP)

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the developers or project managers beyond proving that “usefulness was useful”. The overly simplistic TAM did not possess the required explanatory power to guide neither the development nor the deployment. Unlike TAM, DOI or UTAUT, which only explain technology adoption; TRA and TPB are theories explaining any human behaviour, as such they can easily be adopted for citizen adoption behaviour. The firm theoretical roots of these theories make them ideal as a base model. 2.2.1

Theory of Planned Behaviour

Theory of Planned Behaviour is a theory in social psychology, explaining human behaviour defined in context (Ajzen, 1991). Ajzen defines Theory of Planned Behaviour as an extension of Theory of Reasoned Action (Ajzen & Fishbein, 1972) – which formed the foundations of TAM – developed to overcome the issues in the original theory related to person's control over the behaviour in question. The actual performance in TRA was dependent only on the motivation of the individual. In TPB however, actual performance of a behaviour is affected by the capability and the motivation of the individual.

Figure 2: Theory of Planned Behavior Intentions are a major determinant of actual performance in the theory of planned behaviour and their role in predicting actual performance has been empirically validated (Pavlou, 2003). Intentions capture the motivational factors that drive a person to perform a behaviour. In a sense, intention is a measure of effort an individual is ready to exert to accomplish a behaviour. Intentions can only affect the behaviour to the extent that the person's actual behaviour al control allows them to. Availability of resources and opportunities – actual behaviour al control – required to perform the specified behaviour dictate the actual performance to the extent that the person in question is motivated to try. Perceived behaviour al control – the differentiating point of TPB – measures the perceived difficulty of performing a specific behaviour. Ajzen (1991) likens his PBC construct to Bandura's self-efficacy construct. Yet in time, studies managed to identify another factor determining the PBC, controllability. Perceptions of self-efficacy related to the individuals’ judgments of their abilities where as controllability refers to the individuals’ judgments of the availability of resources. In (Ajzen, 2002b), Ajzen answered claims against the unitary nature of PBC by stating that even though PBC is composed of separable components it is still a unitary construct. According to the same article, both self-efficacy and controllability belief items must be included in PBC measures. According to TPB, PBC affects the performance both directly and through intentions, but the size of the direct effect is proportional to the compatibility between perceived and actual control. In TPB, the intention to perform a specific behaviour is preceded by attitudes, subjective norms and as previously discussed perceived behaviour al control. The weights of each construct in determining the intention depends on the context and the nature of the behaviour in question. The role of attitudes is to Kanat, İrfan Emrah and Özkan, Sevgi Explaining Citizen Adoption Of Government to Citizen Services: A Model Based on Theory of Planned behaviour (TBP)

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capture the individual's evaluation regarding a specific behaviour where as subjective norms capture the social pressure on performing or not performing the behaviour. The attitudes have been proven to influence the intentions; subjective norms however have played a controversial role in online settings. (Venkatesh et al., 2003) for example, found social norms to be only significant (and slightly at that) in mandatory settings or for the initial use of the system where the experience is low. The constructs detailed so far suffice for the prediction of behaviour, but the explanatory power of the model stems from the expansion facilities of TPB. The belief composites provide the researcher with the ability to investigate the salient factors and their effects on the behaviour. Ajzen (1991) lists three types of these salient beliefs each pertaining to a higher level construct; behaviour al beliefs which influence attitudes, normative beliefs which influence the subjective norms and control beliefs which influence the perceived behavioural control. These belief constructs have a dual nature; for each belief composite, a subjective probability and a subjective impact must be measured. It is the combination of the perceived probability with the perceived impact that produces the overall effect of a belief composite, hence the name. For the behaviour al beliefs the probability of occurrence is the belief strength and the impact is the outcome evaluation, similarly in control beliefs these are translated into control belief strength and control

belief power. The formula for the calculation of behaviour al belief composite is A B ∝∑ bi ei . A B stands for attitude towards behaviour , bi stands for behaviour al belief strength and e i for

outcome evaluation. Please compare this to the formula for control belief composite PBC ∝∑ c i p i . In this formula PBC stands for perceived behaviour al control, c i for control belief strength and

p i for control belief power. As can be seen from these formulas the predictor variables are proportional to the sum of factors of impact and probability in every measured instance. 2.3

Additional Constructs

The base models discussed above have generally been expanded with a set of additional constructs the most common of these additional constructs have been discussed below. Figure 3: Dimensions of e-government adoption

Reflecting on the multidimensional nature of e-government phenomena, these constructs will be grouped under three dimensions: Technology, Trust and Localization.

Kanat, İrfan Emrah and Özkan, Sevgi Explaining Citizen Adoption Of Government to Citizen Services: A Model Based on Theory of Planned behaviour (TBP)

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2.3.1

Technology Beliefs:

As previously mentioned in section 2.2 the discussion of base models, technology adoption literature where most of these models originate, had consistently found usefulness and ease of use to be salient in technology adoption. These constructs have also been empirically proven in e-government studies (Carter & Bélanger, 2005; Carter & Weerakkody, 2008; Gefen et al., 2002). 2.3.2

Trust Beliefs

Trust is reported to be a key enabler in impersonal situations with a level of uncertainty, online environments are no exception. Belanger & Carter (2008) and DESA (2008) list the lack of trust as one of the factors impeding the adoption of e-government services. As Gefen, Karahanna & Straub, (2003) noted, there is no agreement on the definition of trust. While trust had generally been regarded as a unitary construct (Rotter, 1967), defining trust as a composite structure is gaining support (McKnight, Choudhury & Kacmar, 2002; Gefen et al., 2003). There also is distinction between types of trust, among the many listed in literature the ones related to this study are party based trust (trust in a certain trustee) and institutional trust (trust stemming from environmental conditions). McKnight et al. (2002) conducted a study based on TRA in which fifteen different beliefs relating to trust were identified in a total of thirty two studies. Eleven of these beliefs were clustered into three major trusting beliefs – namely: integrity, benevolence and competence – forming an integrative typology. As can be seen, these relate to the attributes of the trustee. Even though Mc Knight used the typology to measure both party based and institutional trust, this typology is more suited to measure party based trust. Trust according to McKnight is based the trustee’s beliefs on the integrity, competence and benevolence of a trustee. Integrity is the belief that trustee will keep his promises. Competence is the belief that the trustee is capable of performing as expected. Benevolence is the belief that trustee will be caring towards the trustee and will not act opportunistically. Gefen et al. (2003) defined institutional trust based on Shapiro (1987) as a sense of safety caused by the impersonal structures. Institutional trust has two dimensions, situational normality and structural assurances. Situational normality refers to the perceptions that relate to an expectation of success based on contextual normality. The internet – being the infra structure of e-government - is still a source of uncertainty for some countries and the citizens trust or the lack there of in the infrastructure would affect the use of e-government services (Carter & Bélanger, 2005). This factor might not be as evident for countries that are advanced in terms of ICT but the inclusion would still provide valuable insight for cultural comparison. Throughout this text the trust in the internet refers to the institutional trust in e-government context. Risk comes to mind as a natural extension of trust and it has also been included in a number of studies (Gefen et al., 2002; Pavlou, 2003; Belanger & Carter, 2008) but a consistent result could not be derived. Also as pointed by Pavlou (2003) the direction of relation between risk and trust is unclear and the effects of Risk can be mediated in Trust or the two may seriously overlap. Thus the inclusion of risk would require caution. 2.3.3

Localization

To account for the differences among the distinct social strata in a country or among different countries a facility must be included in the model. The most evident and easily measurable source of the difference is usually the position of the sample in ICT divide. Carter & Weerakkody (2008) used the skills, the use of a computer, and the access, the availability of a computer, for this purpose. They observed that in developed countries skills and technology required to access the e-government services are ubiquitous and transparent to citizens of such countries. Thus the effects of skills and access to technologies will prove to be less significant in comparison to developing countries. Kanat, İrfan Emrah and Özkan, Sevgi Explaining Citizen Adoption Of Government to Citizen Services: A Model Based on Theory of Planned behaviour (TBP)

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3

RESEARCH METHOD

The proposed model is an implementation of TPB with the additional constructs integrated as salient beliefs. Even though, it is possible to arrive at predictions about the actual usage by adopting only the questionnaire items for the major constructs of TPB to the specific implementation at hand, without investigating the salient beliefs the results will prove nothing about the reasons of the behaviour. Ajzen (1991) recommended eliciting salient beliefs for each study. Yet this would produce a sample specific belief set, unfit for inter-cultural comparisons or even comparisons among different samples. For the generalizability purposes, beliefs are drawn from constructs that are proven in the literature to be effective in the broadest context possible. Since these constructs can serve as more than one belief type (Perceived ease of use is both a behavioural and a control belief for example) the relationships between the constructs in the model will be given below in the form of hypotheses. 3.1

Basic hypotheses formulated

The basic hypotheses are the relations between major constructs of TPB, these are integrated into the model as Ajzen (1991) envisioned. H1*: The intention to use an e-government service positively influences the actual usage of the service. H2a: Perceived Behaviour al Control over using an e-government service positively influences the intention to use the service. H2b*: Perceived Behaviour al Control over using an e-government service positively influences the actual usage of the service. H3: Attitude towards using an e-government service positively influences intention to use the egovernment service. H4: Subjective norms regarding the use of an e-government service will have a positive effect towards the intention to use the service. The following hypotheses are proposed depending on the belief types. 3.2

Secondary hypotheses formulated

The secondary hypotheses relate to the additional constructs and their respective beliefs. These constructs on which the secondary hypotheses are based have been presented in section 2.3 within literature review. 3.2.1

Technology

Perceived Usefulness: According to (Davis, 1989) PU is the extent to which the use of the product will enhance one's performance in performing a task. In our case, perceived usefulness of using an egovernment service is the extent to which a citizen believes, using the e-government service would enhance her efficiency. The effect of PU on intentions over the attitude had been shown by (Davis, 1989). Hence, the following: H5: Perceived Usefulness of an e-government service will have a positive effect on the attitude toward the use of e-government service. Perceived Ease of Use: Davis(1989) defined perceived ease of use as the extent to which the use of a product will be free of effort. In this study, perceived ease of use pertains to citizen's beliefs regarding to the use of an e-government service will be free of effort. Davis (1989) proved that PEOU influenced intentions over attitudes. Based on this, the following is proposed: Kanat, İrfan Emrah and Özkan, Sevgi Explaining Citizen Adoption Of Government to Citizen Services: A Model Based on Theory of Planned behaviour (TBP)

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H6a: Perceived Ease of Use of an e-government service will have a positive effect on the attitude toward the use of e-government service. Beyond the attitudes, PEOU also influences PBC. Since (Davis, 1989) used Bandura's self-efficacy to support his PEOU construct it can be concluded that self efficacy is a determinant of PEOU. Ajzen (1991) was also influenced by Bandura's research when forming PBC. Thus they are theoretically connected. The relationship between PBC and PEOU is more than evident when it is put in this way: they both translate into a reduction in effort required to perform a task. Thus, the following hypothesis is proposed: H6b: Perceived Ease of Use of an e-government service will have a positive effect on the perceived behaviour al control of the e-government service. 3.2.2

Trust

Trust in e-Government: Party based trust plays a role in the attitudes of the citizens by enhancing their expectations of the outcomes. (Ajzen & Fishbein, 1972) formulates attitudes as a factor of outcome expectations and outcome values. Thus by manipulating expectations it is possible to manipulate attitudes. It has also been empirically shown in both e-commerce (Gefen et al., 2003; Pavlou, 2003; Pavlou & Fygenson, 2006) and e-government (Carter & Bélanger, 2005; Carter & Weerakkody, 2008) that party based trust plays an important role. H7a: Trust in e-Government providing the e-government service will have a positive effect on the attitude toward the use of e-government service. Trust in e-government also influences PBC through reducing the complexity and increasing the perceived control over the situation (Pavlou & Fygenson, 2006). H7b: Trust in e-Government providing the e-government service will have a positive effect on the perceived behaviour al control of e-government service. Trust in Internet: Structural assurances and situational normality create a perception of safety based on the guarantees and safety nets. In other words, if a citizen perceives the safety measures – such as encryption of sensitive data, or the legal frame work surrounding online transactions – he will be more likely to use the e-government service. Trust of internet belief type is a combination of these two belief types. The same mechanism discussed in trust in e-government also applies here translating trust of internet to attitudes and behaviour al control towards e-government usage. H8a: Trust in internet will have a positive effect on attitude to use e-government service H8b: Trust in internet will have a positive effect on perceived behaviour al control to use egovernment service 3.2.3

Localization

Skills: As laid out by Ajzen (2002b), the perceived behaviour al control construct is a unitary construct combining self efficacy and locus of control. Beliefs of a citizen's skills regarding the use of a technology directly relate to the citizen's self-efficacy beliefs and have an effect on PBC. H9: The skills will have a positive effect on the perceived behaviour al control of an e-government service. Access: Beliefs regarding to the access to technology affect the PBC through controllability beliefs of the citizens. H10: The access will have a positive effect on the perceived behaviour al control of an e-government service. Kanat, İrfan Emrah and Özkan, Sevgi Explaining Citizen Adoption Of Government to Citizen Services: A Model Based on Theory of Planned behaviour (TBP)

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3.3

Proposed Model

All the constructs in the proposed model and the relations between these constructs can be seen in the figure below. As can be seen the proposed model covers almost all of the reasons of failure listed in (DESA, 2008).

Figure 4: Proposed model of e-government adoption

3.4

Instrument Development

A measurement instrument to empirically validate the proposed model is necessary. Ajzen (2002c) lays out the ground work for developing a TPB questionnaire. According to Ajzen, combining items from various studies might harm the internal consistency of the model. To prevent this, the compatibility of the items in the study must be ensured by structuring them to reflect a specific behaviour defined in terms of Target, Action, Time and Context (TACT). The measures employed in this study were drawn from literature and adopted into the study to fit the selected context and the requirements of TPB. Predictor variables – subjective norms, attitudes, perceived behaviour al control and intentions – were adopted from (Ajzen, 2002a) Belief composites for technology beliefs were adopted from (Davis, 1989), the trust beliefs were adopted from (McKnight et al., 2002), localization beliefs were adopted from (Carter & Weerakkody, 2008). Since these items were to be integrated into the model as belief composites they had to be rewritten to be compatible with TPB belief composites. Five point likert scales were employed for all these constructs with 1 denoting a negative answer and 5 a positive answer. The questionnaire also collected basic demographic data. The researchers reviewed resulting items to ensure the meaning was preserved through adoption and translation to Turkish. In the end of the instrument development a total of 81 questions were in the scale. As suggested by Ajzen (2002b), multiple questions for each variable were developed which were refined through the pilot study.

Kanat, İrfan Emrah and Özkan, Sevgi Explaining Citizen Adoption Of Government to Citizen Services: A Model Based on Theory of Planned behaviour (TBP)

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3.5

Pilot Study Data Collection

The survey instrument was administered on-line to a convenience sample of fifty people. A total of forty-eight responses were collected during the pilot study. Of these forty-eight responses, twelve were incomplete and were unfit for any analysis; four out of the remaining thirty six valid responses were only complete up to the major constructs and were thus excluded from the belief composite analysis.

4

RESULTS

The results presented in this paper are derived from the pilot study findings. Thirty-five percent of the respondents who participated in the pilot study were female. The age of the respondents were between twenty – thirty years with a median age of twenty-six and a mean of 25.77. Forty percent of the respondents reported that they spend more than seven hours each day on-line, followed by five to seven hours with twenty-five percent. All responses indicated an internet use that is more than an hour-a day. All respondents reported that they used the internet to receive some services. Ninety-one percent used the internet for banking, seventy-one percent for shopping and sixty-five percent for egovernment services. The data collected in the pilot study were analysed by R, an open source statistical computing environment (R Development Core Team, 2008). The outliers within the data set were eliminated from the sample. Next, the data set was tested to see if there was any difference between the respondents that had previous experience with the system and the ones that had not. Welch's two-sample T-test in R was used with a confidence interval of ninetyfive percent on all items in the scale. None of the items showed a statistically significant difference. Therefore it was concluded that the two samples were statistically the same. In order to test the internal consistency of the items measuring the same construct, Cronbach's alpha measures for each of questionnaire items were calculated. According to (Gliem & Gliem, 2003) a factor loading between seventy to eighty percent points shows a good internal consistency where as a loading above eighty percent indicates an excellent internal consistency. The cronbach's alpha tests revealed that all constructs except for one had alpha values above seventy percent, and only four of the thirteen constructs had alpha values below eighty percent. The results reveal that all constructs had good internal consistency. In the light of the reliability tests, nine items and a total of fourteen questions were removed from the instrument. For alpha test results see the table below. Construct

Alpha Value

Intention

0.79

Attitude

0.87

Subjective Norms

0.84

Perceived Behavioural Control

0.68

Perceived Usefulness (behavioural belief)

0.70

Perceived Ease of Use (behavioural belief)

0.92

Trust of Government (behavioural belief)

0.80

Trust of Internet (behavioural belief)

0.79

Perceived Ease of Use (control belief)

0.82

Trust of Government (control belief)

0.81

Trust of Internet (control belief)

0.84

Access (control belief)

0.80

Skills (control belief)

0.71

Table 2: Cronbach's Alpha Results for Constructs Kanat, İrfan Emrah and Özkan, Sevgi Explaining Citizen Adoption Of Government to Citizen Services: A Model Based on Theory of Planned behaviour (TBP)

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Descriptive statistics of the regarding the constructs can be found below. The ranges of major constructs and belief composites differ due to the calculation method of belief composites in TPB. Construct

n

Mean

Sd.

Range

Intention

35

1.29

0.59

-2 , +2

Attitude

35

1.42

0.51

-2 , +2

Subjective Norms

34

0.91

0.69

-2 , +2

Perceived Behavioural Control

36

1.19

0.60

-2 , +2

Perceived Usefulness (behavioural belief)

30

4.93

1.98

-10 , +10

Perceived Ease of Use (behavioural belief)

32

3.49

2.55

-10 , +10

Trust of Government (behavioural belief)

31

3.87

1.79

-10 , +10

Trust of Internet (behavioural belief)

31

4.26

2.12

-10 , +10

Perceived Ease of Use (control belief)

29

4.18

2.22

-10 , +10

Trust of Government (control belief)

30

3.34

1.83

-10 , +10

Trust of Internet (control belief)

29

4.16

2.13

-10 , +10

Access (control belief)

32

5.28

2.56

-10 , +10

Skills (control belief)

30

5.75

3.02

-10 , +10

Table 3: Descriptive Statistics After the data collection of the pilot study the questionnaire was altered to eliminate any possible misunderstandings. The description of some tasks and minor wording details in survey items have been altered according to the feedback from the subjects.

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CONCLUSIONS AND LIMITATIONS

This research is still in progress. A model as presented in this paper has been proposed and the instrument to test this conceptual model has been developed. The results presented in this study are based on the pilot study, with a rather small sample size and cannot be generalized. The descriptive statistics of the pilot study cannot be interpreted without further analysis. The actual measurements and their analysis have not been completed. Once the data collection is completed, the gathered data will be analysed using both structural equation modelling (SEM) or partial least squares (PLS) according to the sample size to derive conclusive results regarding the validity of the model. Until then, the hypothesis testing cannot be completed. At the time of this conference the researchers of this paper have reached to 230 respondents. The preliminary results seem promising in validating the research model proposed and the researchers will share their findings during the conference.

References AlAwadhi, S. & Morris, A. (2008). The use of UTAUT Model in the Adoption of Egovernment Services in Kuvait. In , Proceedings of the 41st Havaii International Conference on System Sciences. Ajzen, I. (1991). The Theory of Planned Behaviour . Organizational Behaviour and Human Decision Processes, 50, pp. 179-211. Ajzen, I. (2002a). . Retrieved from people.umass.edu/aizen/pdf/tpb.questionnaire.pdf. Ajzen, I. (2002b). Perceived Behaviour al Control, Self-Efficacy, Locus of Control, and the Theory of Planned Behaviour . Journal of Applied Social Psychology, 32, pp. 665-683. Kanat, İrfan Emrah and Özkan, Sevgi Explaining Citizen Adoption Of Government to Citizen Services: A Model Based on Theory of Planned behaviour (TBP)

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European and Mediterranean Conference on Information Systems 2009 (EMCIS2009) July 13-14 2009, Crowne Plaza Hotel, Izmir

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Kanat, İrfan Emrah and Özkan, Sevgi Explaining Citizen Adoption Of Government to Citizen Services: A Model Based on Theory of Planned behaviour (TBP)

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