E-Government In Mauritius: A Principal Component Analysis

Abstract

E-government has made the public sector more accessible, efficient, transparent and responsive to grievance. This paper investigated into these aspects through the principal component analysis to make interpretations of several variables easier for policy makers. A random survey among 244 e-government users was conducted across all districts of Mauritius. The Kaiser-Meyer-Olkin measure of sampling adequacy is 0.85. The determinant of R-matrix exceeds 0.00001 and the Barlett’s test is highly significant (p<0.001). An oblique rotation has been done. This study reveals four subscales of e-government: ‘democratic channel’, ‘e-interaction’, ‘website quality’ and ‘cyber trust. Around 56% of total variance is explained. The Cronbach alpha of each subscale exceeds the conventional 0.7 level. Through the democratic channel citizens express their views and participate in policy making. E-interaction is about the effectiveness of online dialogue between citizens and various government agencies. Website quality measures the overall experience of citizens towards aspects of navigation, comprehensiveness, information and content. Cyber trust emphasises the importance of having secure government websites. If the government pays inadequate attention to these subscales, citizens would eventually be dissatisfied and become slow at accepting e-government initiatives. They would feel frustrated with unclear content, abandon government e-portal and feel excluded from policy making;

Keywords: E-governmentPrincipal Component AnalysisOblique RotationtrustTAM”“UTAUT

Introduction

E-government is the use of ICTs in public service delivery. It has altered the way in which governments and citizens relate to one another by enabling access to government information; doing away with the forty-hour workweek restriction; improving provision of public services; leading to higher customer satisfaction through client orientation; inspiring greater trust in the government; making the public sector accountable, transparent, cost-effective and more responsive to grievances; reducing discretionary powers of ministers and government officials; improving citizen participation in the policy making process while at the same time opening itself up to scrutiny by citizens.

Principal component analysis is a technique that yields an ‘efficient set of regressors’ with reduced numbers of variables to increase degrees of freedom ( Moser, 1984, p. 247) . A high degree of inter-correlation among some variables may suggest that they relate to the same underlying component in which case an explanation of citizens’ perception on e-government may be based on fewer but more fundamental independent factors than on the original larger number of variables. A model with the large number of original independent variables that explains a higher percentage of variation has little theoretical meaning as it causes confusion instead of explaining the phenomenon in question ( Li, 1970) . Each principal component is ranked according to the amount of variation it explains in the original set of variables. Although the use of principal component analysis is only exploratory it may be used to guide future studies and inform policy making.

Citizens basically value e-government in Mauritius in terms of the government ‘website quality’, its ability to act as ‘democratic channel’, its promise of upholding ‘cyber trust’ and acting as a platform for ‘e-interaction’ between the citizens and the government. The rest of this paper is structured as follows: first a theoretical and empirical review of the existing literature on e-government is provided, followed by some research questions after which the purpose of this study is clearly stated. The methodology is then explained and justified at length. The subsequent section discusses all results. To conclude this paper all theoretical and policy implications will be fully discussed and some suggestions that may guide future studies in the field of e-government will be made.

Problem Statement

Theoretical frameworks

The literature consists of several models that explains e-government use and these include the theory of reasoned action, motivational model, theory of planned behavior, combined TAM and TPB, model of PC utilization, innovation diffusion theory, social cognitive theory, the technology acceptance model (TAM), the unified theory of acceptance and use of technology (UTAUT). The TAM and UTAUT model are however most commonly used as they were designed to account for shortcomings in other models. Both have overlapping constructs, for example relative advantage of the diffusion of innovation theory and perceived usefulness of the TAM renamed as performance expectancy in the UTAUT model ( Carter & Belanger, 2005) . They may however be conceptually distinct.

The UTAUT was created after accommodating the conceptual and empirical similarities of eight models of technology acceptance in the IS literature ( Venkatesh, Morris, Davis, & Davis, 2003) . It revealed that four components: Performance expectancy, effort expectancy, social influence and facilitating conditions were determinants of behavioural intention. Performance Expectancy is the extent to which e-government use would enable the individual to improve his/her job performance. Effort expectancy is the extent to which e-government services are easy to use. Social influence is the extent to which the individual believes that people important to him/her feel that he/ she should use government websites. Facilitating conditions are the extent to which infrastructures exists to support e-government use. The two widely acknowledged components of the TAM model are the perceived ease of use (PEOU) and perceived useful (PU) whereas the UTAUT contains elements of social pressure and monetary aspects in terms of facilitating conditions which are non-existent in TAM.

Perceived usefulness is about the belief that the innovative technology will allow citizens to accomplish their tasks, that is the extent to which time may be saved and extraction of information may reduce costs ( Shih, 2004) and the degree to which the website provides all information. Perceived usefulness is enhanced as the citizen need not be aware of the various government departments and the services they each provide but he/she can still access all services from one access point, the government web portal. Perceived ease of use is the extent to which an individual believes that use of ICT in the delivery of public services would be free of effort, that is, the ease associated with learning and becoming skilful at using government websites which depends on how clear, understandable and flexible these websites are ( Davis, 1989) . When it is easy to use a technology, it is perceived as being useful and one develops a positive attitude towards it. These increase a person’s intention to use the technology and eventually actual use increases ( Taylor & Todd, 1995) .

However these theories explain mainly the adoption of innovation or the use of technology. E-government is beyond the mere adoption of technology and several other aspects such as trust in the government, trust in government departments, the extent to which government officials respond to citizens’ demand and meet their expectations are important factors that ultimately encourages the use of digital government. These are further discussed in the next subsection.

E-government constructs

A good government website encourages e-government adoption. The fundamental role of government websites should therefore be about enabling citizens to access all government departments at one access point and at their own conveniences ( Schuppan, 2009) . Thus, citizens do not need to travel long distances to go to several government offices in search of government services. Also a good user interface should be simple, pleasant, easily navigable, usable, understandable and regularly updated. Designing an appropriate user interface can be a challenging task. Lim, Song and Lee (2012) report that the usability of an user interface contributes to its user-friendliness as users may work in an efficient, manageable and effective way. User-friendly interfaces may help e-government users to interact better with the government information available online. Galbraith (1973) stresses upon the availability of adequate online information to enable the users to complete their tasks. Sub-tasks with ill-defined and fuzzy structures would increase the complexity of tasks ( McKeen, Guimaraes, & Wetherbe, 1994) . In line with these principles, the government website should therefore show an obvious start with clear exit ( Blair-early & Zender, 2008) , be well-designed, speak the citizen’s language, minimize the citizen’s memory load, provide shortcuts and strive for consistency. Also clear and simple labels would improve clarity. If citizens cannot understand or follow instructions easily on the government websites, they would feel frustrated and abandon its use. Basically the idea behind government websites is to enable citizens to interact with the government but if they cannot figure out how the websites work, then all investment in e-government projects would be void. The way in which information is presented is also critical to stimulate the user’s citizen’s involvement ( Griffith, Krampf, & Palmer, 2001) . Alsheri, Drew, & AlGhamdi (2012) advocates website quality as a determinant in explaining user acceptance of e-government services.

The use of the computer interface provides new possibilities of transaction between the provider and the consumer ( Griffith, Krampf, & Palmer, 2001) . The level of citizen satisfaction is linked to the availability of reliable and relevant information on the government web portal. According to Kumar, Mukerji, Butt, & Persaud (2007), online service quality may be analysed in terms of the quality of content available on the government web portal and how quickly the citizen receives an answer with a problem-solving approach. The quality of content such as the availability of searchable databases, audio and video clips help the citizen to process government information actively, eventually leading to a positive response from the citizen and continued use of the digital channel to interact with the government. Citizens’ needs should take precedence over departmental structures and thus, government websites should be organized on the user perspective approach. Also the need to provide ‘a readily accessible overall mechanism for assistance’ to users has been highlighted ( Blair-early & Zender, 2008, p. 102) . Support should be available as the need arises and it should be easy to find with simple instructions that users can follow. E-government should enable the provision of real time and good service quality ( Alsheri, Drew, & AlGhamdi, 2012) . Online communication between citizens and the government should be both effective in terms of timely delivery what is required by the former and efficient in terms of time saved and cost reduction.

The importance of trust has been widely acknowledged in many studies (Alasem, 2015; Alomari, 2014; Nabafu & Maiga, 2012; Warkentin, Gefen, Pavlou & Rose, 2002). Trustworthiness is defined as the confidence placed in the online marketer’s integrity and reliability (Carter & Belanger, 2005). McKnight, Choudhury, & Kacmar (2002) advocate the need for structural assurance, for example regulations, legal procedures and promises to promote success. As reported by Sanmukhiya (2018), in the absence of trust, a citizen would not reveal his/her personal information and engage in a virtual environment to transact with the government. Amongst other factors, it has been reported that trust in the government itself, information security, transaction security and perceived risks (Rehman, Kamal, & Esichaikul, 2012) reliability and integrity for the provisions of e-government services (Carter & Belanger, 2005), accountability (Belwal & Al-Zoubi, 2008) and confidence in the technology used by an institution (Jahangir & Begum, 2008) are of paramount importance to ensure the use of e-government services. E-government use is highly influenced by the extent to which people feel that the government online portal is safe and can protect their information against intrusion (Papadomichelaki & Mentzas, 2011) or against misuse by third party. Without trust, citizens would only engage with the basic e-government activities such as searching for information online, downloading documents and making enquiries. They would be unwilling to insert their credit cards details on government websites and would not conduct online transactions with the government (Sanmukhiya, 2018).

Schuppan (2009) argues that e-government is not restricted to the mere provision of public services but it extends to democracy given that it enables new forms of participation into the policy making process. Citizens, for example, may access new information and be consulted on current issues or propose legislation amendments. Here e-government acts as a ‘democratic channel’. In short e-government provides adequate venues such as discussion forums and chat rooms to encourage citizens’ participation (Tolbert & Mossberger, 2006). Nevertheless some studies reported that government websites do not act as a vehicle for democratic dialogue and citizens do not participate in the decision making process (Al Athmay 2013; Sanmukhiya 2018). The lack of citizen involvement and consultation have been highlighted at the initial stages of policy making such as during conceptualization and planning which eventually renders e-government initiatives difficult during the implementation stage (Das, Patra, & Panda, 2011). Governments may learn from the effectiveness of the electronic bulletin board initiated in Fijisawa to gather feedback and other cost-effective policies from the citizens (Shim & Eom, 2008). This process is expected to increase citizens’ trust in both the government itself and its agencies, and encourage the much needed collaboration between the citizens and policy experts. Through the democratic channel, e-government empowers citizens.

Research Questions

This research investigates the various constructs of e-government and the perceptions of Mauritian citizens toward each construct. It may be argued that the concept of e-government has evolved over the decades to such a large extent that theoretical concepts such as the Technology Acceptance Model (TAM) and the Unified Theory of Acceptance and Use of Technology (UTAUT) may no longer explain the reasons behind the adoption of e-government unless these are modified.

Purpose of the Study

E-government is neither a single nor one-dimensional matter. It assumes multiple components which have a range of measurable attributes. The purpose of this paper is to investigate into these aspects of e-government through the exploratory factory analysis. This study based in Mauritius uses the principal component analysis in the field of e-government to make interpretations of several variables easier for policy makers by reducing them into some related sub-components of e-government.

Research Methods

Initially the researcher did an intensive reading on e-government so as to identify the relevant aspects that should be covered in a survey. Then a questionnaire which contained 21 likert-type items with a five point response scale (strongly disagree, disagree, neither agree nor disagree, agree and strongly agree) was designed to measure perceptions of citizens towards government websites in Mauritius. Participants were asked to tick one option that best explained their perceptions for each question. A pilot study was initially conducted among 21 users of government websites to test for ambiguous items in the questionnaire and to ensure that all aspects of e-government use which are valued by citizens were incorporated. The final questionnaire was modified accordingly. Data were then randomly collected among 244 citizens who claimed to use government websites. These data were collected across all districts of Mauritius irrespective of age, gender, occupation, rural/urban dwellings, qualification and income to ensure a nationally representative data set.

All questionnaires were administered on a face to face basis, allowing the researcher to go beyond the traditional mere ticking of options on the likert scale. The participants had the opportunity to explain their answer and express their views on e-government in Mauritius. The native language ‘Creole’ was used to avoid all misunderstandings. Data were collected only from those citizens who were willing to participate in the survey. Any participant could terminate this survey at any time without providing any justifications. Such data were not coded as these questionnaires were immediately destroyed.. Also no attempt was made to trace any of the respondents after they had filled in the questionnaires. All data were kept anonymous and confidential. The Statistical Package for Social Sciences was used to analyse all data for the current study.

As argued by Albaum (1997), likert-type items may not be analysed separately as these are intended to be used as summated scale. A statement on its own cannot capture the essence of what the questionnaire as a whole is designed to measure. Thus, in an attempt to identify reliable and valid constructs of e-government use from the questionnaire, the exploratory factory analysis was used. This approach did not only reduce several variables into related sub-components, it also made interpretations of citizens’ perceptions towards the Mauritian government web portal easier. Although the principal component analysis is not an exploratory factory analysis method, it was deemed most appropriate as it is the most popular method used in the literature for variable reduction (Howard, 2016) and both procedures often generate similar results (Field, 2009).

Sample size is of paramount importance when assessing the reliability of factor analysis. Unlike the research conducted by Farell, Sapp, Johnson, & Pollard (1994), the current study does not have 250 participants and the mean communality is less than 0.60. But it exceeds a minimum of 200 subjects and the 5 participants to 1 variable ratio as recommended by Howard (2016). It also exceeds the 10 participants to 1 variable ratio advocated by Nunnally (1978). Thus the sample size in the current study is adequate to yield reliable factors. Alternatively the Kaiser-Meyer-Olkin (KMO) measure of sampling adequacy has been computed.

It was hypothesized that latent constructs were correlated with one another to some extent given that all items on the questionnaire were initially meant to capture citizens’ perceptions about some related dimensions of e-government in Mauritius. This assumption is theoretically justified especially in the case of naturalistic data where psychological constructs are correlated (Field, 2009). The oblique rotation ‘direct oblimin’ was selected based on the fact that underlying factors might correlate and unlike the ‘promax option’ it is appropriate for the sample size in the current study. Finally the Cronbach alpha was calculated to examine the reliability of each factor.

Findings

Demographic features of respondents

As displayed in Table 1 , male participants outnumbered female participants by around 12%. This is in line with other studies conducted on ICT and e-government adoption. Men are believed to be more likely than women to adopt ICT and as a result use government websites relatively more than women (Rodrigues, Sarabdeen & Gil-Garcia, 2016; Avgerou, 2003; Owolabi, 2013; Venkatesh, Morris & Ackerman, 2000).

Table 1 -
See Full Size >

Around 60% of the government website users were rural dwellers and this may be explained in terms of the more even distribution of ICT infrastructures across all districts in Mauritius (Sanmukhiya, 2017; Ramessur, 2009). The majority of e-government users were aged between 26 to 35 years followed by those aged between 18 to 25 years. Thus around 75% of the sample were young people. The relatively low percentage of old people who participated in the survey may be attributed to the fact that as people grow older they are unlikely to use technology (Choudrie & Lee, 2004; Choudrie & Dwivedi, 2005; Mwangakalla, 2012; Olaitan, 2015). They may lack the necessary basic or IT skills (Mutula, 2008; van Djik, Peters & Ebbers, 2008; Jun & Wang, 2012).

The majority of e-government users, around 50% were private sector employees. During the face to face administration some of these respondents stated that they used the government websites for work purposes, for example, updating themselves on amendments in labour law and downloading documents to apply for business permits. The majority of participants, around 53% had done at least a bachelor’s degree. This is in line with existing studies which report that education is positively related to the use of ICT and e-government services (Al-Shafi & Weerakkody, 2010; Niehaves, Gorbacheva & Plattfaut 2013; Taipale, 2013; Venkatesh, Sykes & Venkatraman, 2014). Less educated citizens tend to use face to face interactions. The characteristics of respondents within the sample used for the current study is in line with the characteristics reported by existing literature. This sample reflects important demographic information of e-government users and thus findings of this paper may be generalized.

Analysis

The KMO value of 0.85 which falls within the range of ‘good’ (Howard 2016) and ‘great’ (Hutcheson & Sofroniou, 1999) implies that latent constructs are present and the sample size is appropriate for factory analysis. Kaiser (1960) recommends retaining all factors with eigenvalues exceeding 1 but Jolliffe recommends retaining all factors with eigenvalues above 0.7 (Joliffe, 1986). Stevens (2002) suggests an alternative method which is to use a scree plot to determine the number of factors to be extracted when the sample size exceeds 200 individuals. Since the current study contains a sample of 244 citizens and fits Stevens’ (2002) requirement for reliable factor extraction, a visual scree plot was used. Also Field (2009) suggested running the PCA with the eigenvalues greater than 1 and generating the scree plot simultaneously. In case of no difference on the number of factors to be retained, the Kaiser’s criterion of eigenvalues greater than 1 may be used. In this study both the scree plot and the Kaiser’s criterion justified retaining four factors. Figure 1 shows the results of the scree plot as it starts to tail off after five components.

Figure 1: Scree plot of eigenvalues
Scree plot of eigenvalues
See Full Size >

Four components were extracted and these were labelled as ‘democratic channel’, ‘e-interaction’, ‘website quality’ and ‘cyber trust’. These explained 55.6% of the total variance in e-government use with mean communality of 0.56. Each component has a Cronbach alpha above the conventional level of 0.7 with inter-item correlations exceeding 0.3, highlighting the internal consistency of each item and good reliability within each component. Thus, factor analysis evaluated construct validity.

Following Field (2009) and Howard (2016), loadings below 0.4 were suppressed. Good factor loadings on a primary factor should be at least equal to 0.4 to represent substantive values. A look at the correlation matrix confirmed that all items correlate rather well with one another. None of the items have excessively large correlation values (for example, above 0.9). The determinant of the correlation matrix exceeded the value of 0.00001 implying that the items in the questionnaire on e-government did not suffer from multicollinearity. The highly significant Barlett’s test of sphericity χ2 (190) = 1708, p<0.001, meant that items on the questionnaire were sufficiently correlated to find clusters and thus the data was suitable for factory analysis. Table 2 reports loadings from the pattern matrix that have been rounded to 2 decimal places along with the eigenvalues, percentage of variance and Cronbach alpha of each of the four factors.

Table 2 -
See Full Size >

Factor 1 measured the overall experience of the citizen who interacted with government websites and included aspects such as the ease of navigation, adequacy of information and clarity of content. It was labelled as ‘website quality’ and explained 29% of the overall variance in citizens’ perceptions towards government websites. This factor has a Cronbach alpha of 0.8 which indicates good reliability and deletion of any item within this sub-scale would not increase reliability. All items correlate well with the subscale ‘website quality’ and they contribute positively to its overall reliability. All item-total correlations are above 0.3 as required by Field (2009). On average citizens have moderate perceptions (3.4±0.7) towards the quality of the Mauritian government e-portal. The website quality construct prioritized comprehensiveness of information followed by the ease of finding information, usefulness of government websites to the user, ease of dealing with the e-portal, adequacy of information provision and finally its capability to serve its purpose. AlSheri, Drew, & AlGhamdi (2012) also found website quality to be an important determinant in the adoption of e-government.

Factor 2 offers an avenue for citizens to express their views and participate in the policy making process from scratch to implementation. It was labelled as ‘democratic channel’ which is in line with the notion of governing with people (Oktem, Demirhan and Demirhan, 2014). It explained around 11% of total variance in the citizens’ perceptions towards the use of government websites in Mauritius. The Cronbach alpha of 0.84 revealed good reliability of this sub-scale. During the extraction of factors one item was dropped due to low loadings (below 0.4). The statement read as ‘E-government increases accountability of politicians and government officers’. This item had a maximum loading of 0.33 on ‘democratic channel’ and the Cronbach alpha of this factor improved from 0.82 to 0.84 once this item was removed from the analysis. All remaining items correlated well with the overall score of the construct ‘democratic channel’ with a mean inter-item correlation above 0.3. The factor structures in the PCA remained unchanged and total explained variance improved from 54.3% to 55.6%. On average citizens had low mean score (2.5±0.8) towards the ‘democratic channel’ factor. This factor prioritized citizens’ say in decision making followed by their ability to guide policy making. Subsequent items were about the attitudes of the government itself, for example valuing the opinions of citizens, consulting them and finally incorporating their input into decision making.

Factor 3 emphasises anti-cybercrime legislations and the importance of having secure and reliable government websites where citizens’ personal details are kept confidential. This factor was labelled ‘cyber trust’ as it relates to trust issues that may arise when interacting with the government online. It contributed 8.5% to the total variance which explained citizens’ perceptions toward the use of government websites in Mauritius. The Cronbach alpha is 0.75 which is above the conventional level of 0.7 (Field, 2009) or 0.6 for exploratory research (Cronbach, 1951). The factor has item-total correlations above 0.3. Together these indicate good internal consistency and reliability of the scale. On average citizens have low perceived value (2.8±0.8) towards the ‘cyber trust’ construct. It prioritized keeping information of citizens confidential followed by trust placed in the website by the citizens, law enactment against cybercrimes and security of revealing personal details on the government web portal. As argued by Kumar, Mukerji, Butt, & Persaud (2007) a secure government web portal is of paramount importance in encouraging its use.

Factor 4 is about the efficient and effective online dialogue among government agencies and between government officials and citizens. It was labelled ‘e-interaction’ and added around 7% to the overall explained variance in citizens’ perceptions towards e-government in Mauritius. The Cronbach alpha of this construct is above the conventional level and implies that all the five items add to the overall reliability of the ‘e-interaction’ construct. Deletion of none of the items on this subscale would improve reliability. All items correlate well with the overall score of ‘e-interaction’. On average Mauritians displayed low mean score (2.8±0.7) revealing the failure of government websites to act as an effective online interactive platform between citizens and government agencies. Thus, contrary to Griffith, Krampf, & Palmer (2001), the Mauritian web portal did not open up new opportunities of transaction between the user and the government. The factor prioritized government officers’ responsiveness to enquiries made by citizens followed by effectiveness of online communication, availability of online support, efficiency aspect of online communication and finally the quality of government services dispensed online.

Figure 2 summarised the twenty items on the questionnaire which clustered together through the PCA in four factors. Theoretically we would expect all factors to be related to some extent.

Figure 2: Proposed E-government Constructs
Proposed E-government Constructs
See Full Size >
Table 3 -
See Full Size >

The assumption of correlated factors was investigated. For independent factors oblique rotation must provide identical results to the orthogonal rotation and the correlation coefficients of all constructs must be equal to zero (Field, 2009). Neither of these conditions was satisfied and as shown in Table 3 , the component correlation matrix revealed that the four factors were interrelated. Also if the correlation values among the factors are around ±0.32, then there is adequate variance to advocate an oblique rotation (Tabachnick & Fidell, 2007; Brown, 2009) in particular for the correlation between ‘e-interaction’ and ‘democratic channel’ followed by the correlation between ‘website quality’ and ‘cyber trust’ along with the correlation between ‘website quality’ and ‘e-interaction’. Also the component correlation matrix is not an identity matrix. None of the correlation coefficients is close to zero. For this data set it was unreasonable to assume independence between factors of e-government use given the overlap in variance among these factors, thus the use of oblique rotation was justified.

The ‘website quality’ (ease of navigation, absence of ambiguity, availability of necessary, clear and comprehensive information) sets the platform for effective ‘e-interaction’ between citizens and government officials (where productive and collaborative interactions take place). Moreover the government web portal would not be useful to citizens unless it inspires trust, provides adequate laws against cybercrimes and removes concerns about privacy and confidentiality (Sanmukhiya, 2018). ‘Cyber trust’ between the user and the technology, for instance, would facilitate productive and constructive online communication and at the same time encourage citizens’ participation in the policy making process through the ‘democratic channel’ where people may express themselves and provide their input into decision making.

Thus theoretical frameworks such as UTAUT and TAM which predict the use of technology may not be appropriate frameworks to explain the adoption of digital government. Several other equally valuable factors such as the level of trust in the technology of the Institution, the effectiveness of online dialogues between citizens and government agencies, and the possibility of engaging in a democratic dialog where people may speak up their minds have now become important aspects that may either encourage or discourage people from using e-government services. Citizens’ relationship with electronic government has become rather complex.

Conclusion

All items on the questionnaire that eventually clustered into ‘website quality’, ‘e-interaction’, ‘democracy channel’ and ‘cyber trust’ were adapted from the extensive literature review carried out for this study on e-government in Mauritius. A principal component analysis was carried out on 21 items with oblique rotation (direct oblimin). The measure of sampling adequacy was deemed good as depicted by a Kaiser–Meyer–Olkin value of 0.85. The determinant of the R-matrix and the Bartlett’s test of sphericity implied that correlations between the items on the questionnaire were neither too low nor too high. They were sufficiently correlated for PCA. After applying the Kaiser’s criterion and examining the scree plot, four factors with eigenvalues greater than 1 were extracted with a combined explained variance of around 56%.

Those items that clustered on the same factors suggested that factor 1 represented the quality of the government website; factor 2 represented an avenue conducive to democracy, that is, the need to cater for citizens’ opinions, seek their input and change government policies accordingly; factor 3 was labelled as cyber trust as it related to online privacy, legislative aspects and trust issues; and factor 4 represented e-interaction, that is, online interaction and responsiveness of government officers. The component correlation matrix revealed that all factors were inter-dependent in particular for items on the ‘e-interaction’ and ‘democratic channel’ constructs. The Cronbach alphas of all four factors suggest good degrees of reliability. Citizens consistently had low mean scores for the e-government dimensions with the exception of the website quality where they displayed moderate and positive perceptions toward electronic government.

If e-government use is to be encouraged in Mauritius, online task complexity should be reduced. Tasks should be well-structured with straightforward instructions ( McKeen, Guimaraes, & Wetherbe, 1994) . The Mauritian government web portal should be easy to navigate and search engines need to be refined so that lists of inappropriate materials do not show on the results of the search button. Government websites should allow the users to find the e-services they seek in a quick and effortless manner, thus avoiding unsuccessful location of information which would decrease the behavioural intention of the citizens to use e-government ( Carter & Belanger, 2005) .

The government may develop educational resources online and provide technical assistance through community centres to help citizens to assess government e-services. Government agencies should develop online services that look like offline services so that citizens do not face difficulty in using the government web portal, for example, downloadable and editable online forms should resemble the familiar paper format available through the traditional face to face method.

Without cyber trust and trust in the government itself, citizens would be slow at adopting e-government initiatives and would resist to changes proposed by the government. The government should therefore show greater transparence about the flow of users’ information once they are inputted online and implement more severe controls on access of these information by government officers.

In the absence of high website quality, citizens would feel frustrated. Unclear content and fuzzy instructions would reduce the usefulness of government websites. Thus, problems such as overly complex, misguiding instructions, static websites, no live chats and inaccessible government web pages should be addressed promptly. If the visitors are unable to find what they are looking for, they will become dissatisfied and spread the word about the non-functionality of the Mauritian government web portal. Along with other people, they may not visit the portal again ( Glazer, 1991) .

The democratic channel is an important aspect of democracy which all e-government initiatives must encourage. High degree of e-interaction would reassure citizens that government officials are responsive and attentive to their complaints causing their satisfaction with government websites to rise. Also mere citizen participation with inadequate influence to bring changes or affect policies may make both the potential and existing users see their participation as a waste of time or political manipulation. Nevertheless the most challenging aspect of e-government would be to tackle diverse needs into a shared, reliable and complete online government portal.

Future research in the field of e-government may include social influence. Social influence has significant impacts on the adoption of e-government services (Malhotra & Galleta, 1999; Venkatesh, Morris, Davis, & Davis, 2003). Also the current study is based only on citizens’ perceptions and hence future studies may include the perceptions of government officials and the administrators of the Mauritian government e-portal.

References

  1. Al-Shafi, S., & Weerakkody, V. (2010). Factors Affecting E-government Adoption in the State of Qatar. European and Mediterranean Conference on Information Systems April 12-13 (pp. 1-23). Abu Dhabi UAE: EMCIS2010.
  2. Al Athmay, A.-A. A. (2013). Citizens' Perceptions Towards E-governance: A Filed Study. International Journal of Social, Behavioural, Educational, Economic, Business and Industrial Engineering, 7(9), 2576-2584. Retrieved from waset.org/Publication/16711
  3. Alasem, A. N. (2015). Privacy and E-government in Saudi Arabia. World Congress on Engineering and Computer Science WCECS. San Francisco, USA.
  4. Albaum, G. (1997). The Likert Scale Revisited: An Alternate Version. Market Research Society, 39(2), 331-348.
  5. Alomari, M. K. (2014). Discovering Citizens Reaction Toward E-government: Factors in E-government Adoption. Journal of Information Systems and Technology Management, 11(1), 5-20. doi:10.4301/S1807-17752014000100001
  6. Alsheri, M., Drew, S., & AlGhamdi, R. (2012). Analysis of Citizens' Acceptance For E-government Services: Applying the UTAUT Model. IADIS International Conferences Theory and Practice in Modern Computing and Internet Applications and Research.
  7. Avgerou, C. (2003). The Link Between ICT and Economic Growth in the Discourse of Development. In M. Korpela, R. Montealegre, & A. Poulymenakou, Organizational Information Systems in the Context of Globalization (pp. 373-386). Boston, USA: Kluwer.
  8. Belwal, R., & Al-Zoubi, K. (2008). Public Centric E-governance in Jordan: A field study of people's perception of e-governance awareness, corruption and trust. Journal of Information Communication and Ethics in Society, 6(4), 317-333. doi:10.1108/14779960810921123
  9. Blair-early, A., & Zender, M. (2008). User Interface Design Principles for Interaction Design. Interaction Design Research in Human-Computer Interaction, 24(3), 85-107.
  10. Brown , J. D. (2009). Choosing the right type of rotation in PCA and EFA. JALT Testing & Evaluation SIG Newsletter, 13(3), 20-25.
  11. Carter, L., & Belanger, F. (2005). The utilization of e-government services: citizen trust, innovation and acceptance factors. Information Systems Journal, 15(1), 5-25.
  12. Choudrie, J., & Dwivedi, Y. K. (2005). The Demographics of Broadband Residential Consumers in a British Local Community: The London Borough of Hillingdon. The Journal of Computer Information Systems, 45(4), 93-101.
  13. Choudrie, J., & Lee, H. (2004). Broadband Development in South Korea: Institutional and Cultural Factors. European Journal of Information Systems, 13(2), 103-114. doi:10.1057/palgrave.ejis.3000494
  14. Cronbach, L. J. (1951). Coefficient Alpha and the Internal Structure of Tests. Psychometrika, 16(3), 297-334.
  15. Das, R. K., Patra, M. R., & Panda, S. K. (2011). Citizen Participation in Rural E-governance: A Case Study in the Indian Context. 5th International Conference on Theory and Practice, (pp. 325-328). Tallinn Estonia. doi:10.1145/2072069.2072129
  16. Davis, F. D. (1989). Perceived Usefulness, Perceived Ease of Use, and User Acceptance of Information Technology. MIS Quarterly, 13(3), 319-340. doi:10.2307/249008
  17. Farell, W. C., Sapp, M. J., Johnson, J. H., & Pollard, D. S. (1994). Assesing College Aspirations Among At Risk High School Students: A Principal Component Analysis. The High School Journal, 77(4), 294-303.
  18. Field, A. (2009). Discovering Statistics Using SPSS (and Sex and Drugs and Rock'n'Roll) (Third ed.). London, UK: SAGE Publications Ltd.
  19. Galbraith, J. R. (1973). Strategies of Organizational Design. Reading , MA: Addison-Wesley.
  20. Glazer, R. H. (1991). Marketing in an Information-Intensive Environment: Strategic Implications of Knowledge as an Asset. Journal of Marketing, 55(4), 1-19. doi:10.2307/1251953
  21. Griffith, D. A., Krampf, R. F., & Palmer, J. W. (2001). The Role of Interface in Electronic Commerce: Consumer Involvement with Print versus On-Line Catalogs. International Journal of Electronic Commerce, 5(4), 135-153.
  22. Howard, M. C. (2016). A Review of exploratory Factor Analysis Decisions and Overview of Current Practices: What We Are Doing and How Can We Improve? International Journal of Human-Computer Interaction, 32, 51-62. doi:10.1080/10447318.2015.1087664
  23. Hutcheson, G., & Sofroniou, N. (1999). The Multivariate Social Scientist. London: SAGE.
  24. Jahangir, N., & Begum, N. (2008). The Role of Perceived Usefulness, Perceived Ease of Use, Security and Privacy, and Customer Attitude to Engender Customer Adaptation in the Context of Electronic Banking. African Journal of Business Management, 2(1), 32-40.
  25. Joliffe, I. T. (1986). Principal Component Analysis. New York: Springer.
  26. Jun, K.-N., & Wang, F. (2012). E-government and Citizen attitude towards local gpvernment in China: Transperency and Capacity in Service Delivery. International Conference at Fudan University, May 25-27. Shanghai: Public Management Research Association.
  27. Kaiser, H. F. (1960). The Application of Electronic Computers to Factor Analysis. Educational and Psychological Measurement, 20(1), 141-151.
  28. Kumar, V., Mukerji, B., Butt, I., & Persaud, A. (2007). Factors for successful e-government adoption: a conceptual framework. The Electronic Journal of E-government, 5(1), 63-76.
  29. Li, W. L. (1970). Principal Component Analysis of Fertility Changes: United States, 1950-1960. Sociological Focus, 4(1), 21-35.
  30. Lim, C., Song, H.-D., & Lee, Y. (2012). Imrpoving the Usability of the User Interface for a Digital Textbook Platform for Elementary-school Students. Education Technology Research and Development, 60(1), 159-173. doi:10.1007/s11423-011-9222-5
  31. Malhotra, Y., & Galleta, D. F. (1999). Extending the Technology Acceptance Model to Account for Social Influence: Theoretical Bases and Empirical Validation. 32nd Hawaii International Conference on System Sciences (pp. 1-14). Mauii: IEEE Computer Society.
  32. McKeen, J. D., Guimaraes, T., & Wetherbe, J. C. (1994). The Relationship Between User Participation and User Satisfaction: An Investigation of Four Contingency Factors. MIS Quarterly, 18(4), 427-451.
  33. McKnight, H. D., Choudhury, V., & Kacmar, C. (2002). The Impact of Initial Consumer Trust on Intentions to Transact with a Web Site: A Trust Building Model. Journal of Strategic Information Systems, 11, 297-323.
  34. Moser, J. W. (1984). A Principal Component Analysis of Labour Market Indicators. Eastern Economic Journal, 10(3), 243-257.
  35. Mutula, S. M. (2008). Comparison of Sub-Saharan Africa's E-government Status with developed and Transitional Nations. Information management and Computer Security, 16(3), 235-250. doi:10.1108/09685220810893199
  36. Mwangakala, H. A. (2012, September 14). The Effect of Demographic Characteristics on Citizens' Usage of Government Websites. Dodoma, Tanzania. Retrieved from http://ssrn.com/abstract=2146597
  37. Nabafu, R., & Maiga, G. (2012). A Model of Success Factors for Implementing Local E-government in Uganda. Electronic Journal of E-government, 10(1), 31-46.
  38. Niehaves, B., Gorbacheva, E., & Plattfaut, R. (2013). The Digital Divide vs. the E-government Divide. In R. J. Gil-Garcia, E-government Success Factors and Measures: Theories, Concepts, and Methodologies (pp. 52-65). Mexico: IGI Global. doi:10.4018/978-1-4666-4058-0.ch004
  39. Nunnally, J. C. (1978). Psychometric Theory (Second ed.). New York: McGraw Hill.
  40. Oktem, K. M., Demirhan, K., & Demirhan , H. (2014). The Usage of E-governance Applications by Higher Education Students. Education Sciences: Theory and Practice, 14(5), 1925-1943. doi:10.12738/estp.2014.5.2051
  41. Olaitan, A. W. (2015). The Contributory Effects of Socio-cultural Factors on E-government Adoption Among Nigerians. Global Journal of Politics and Law Research, 3(1), 91-104.
  42. Owolabi, E. S. (2013). Socio-demographic Factors as Determinants of Access and Use of ICT by Staff of University Libraries in Oyo State. Library Philosophy and Practice, 947.
  43. Papadomichelaki, X., & Mentzas, G. (2011). Analysing E-government Service Quality in Greece. Electronic Government, An International Journal, 8(4), 290-308.
  44. Ramessur, T. S. (2009). Are Mauritians Ready for E-government Services? Government Information Quarterly, 26, 536-539. doi:10.1016/j.giq.2008.12.016
  45. Rehman, M., Kamal, M., & Esichaikul, V. (2012). Determinants of Trust in E-government Adoption: A Case Study of Pakistan. Americas Conference on Information Systems (p. Paper 12). Washington: AMCIS.
  46. Rodrigues, G., Sarabdeen, J., & Balasubramanian, S. (2016). Factors that Infleunce Consumer Adoption of E-government Services in the UAE: A UTAUT Model Perspective. Journal of Internet Commerce, 15(1), 18-39. Retrieved from dx.doi.org/10.1080/15332861.2015.1121460
  47. Sanmukhiya, C. (2017). E-government Divide in the Republic of Mauritius. International Conference on Social and Management Sciences, Theoretical and Practical Approaches (p. Forthcoming). Singapore: GI Social Sciences Forum.
  48. Sanmukhiya, C. (2018). E-governance dimensions in the Republic of Mauritius. International Journal of Economic Research, Forthcoming.
  49. Sanmukhiya, C., & Roopchand, B. (2016). E-government Non-adoption in the Republic of Mauritius. 5th International Conference on Studies in Humanities and Social Sciences (SHSS-2016). 1, pp. 63-70. Singapore: Emirates Research Publishing Limited.
  50. Schuppan, T. (2009). E-government in developing countries: Experiences from sub-Saharan Africa. Government Information Quarterly, 26, 118-127. doi:10.1016/j.giq.2008.01.006
  51. Shih, H. P. (2004). An Empirical Study on Predicting User Acceptance of E-shopping on the Web. Information and Management, 41(93), 351-368. doi:10.1016/S0378-7206(03)00079-X
  52. Shim, D. C., & Eom, T. H. (2008). E-government and Anti-corruption: Empirical Analysis of International Data. International Journal of Public Administration, 31(3), 298-316. doi:10.1080/01900690701590553
  53. Stevens, J. P. (2002). Applied Multivariate Statistics for the Social Sciences (Fourth ed.). Hillsdale, NS: Erlbaum.
  54. Tabachnick, B. G., & Fidell, L. S. (2007). Using multivariate statistics (Fifth ed.). Upper Saddle River, NJ: Pearson Allyn & Bacon.
  55. Taipale, S. (2013). The Use of E-government Services and the Internet: the Role of Socio-demographic, Economic and Geographical Predictors. Telecommunications Policy, 37(4/5), 413-422. doi:10.1016/j.telpol.2012.05.005
  56. Taylor, S., & Todd, P. A. (1995). Understanding Information Technology Usage: A Test of Competing Models. Information Systems Research, 6(2), 144-176. doi:1047-7047/95/0602/0144/$01.25
  57. Tolbert, C. J., & Mossberger, K. (2006). The Effects of E-government on Trust and Confidence in Government. Public Administration Review, 66(3), 354-369. doi:10.1111/j.1540-6210.2006.00594.x
  58. van Dijk , J. A., Peters, O., & Ebbers, W. (2008). Explaining the Acceptance and Use of Government Internet Services: A Multivariate Analysis of 2006 Survey Data in the Netherlands. Givernment Information Quarterly, 25, 379-399. doi:10.1016/j.gip.2007.09.006
  59. Venkatesh, V., & Davis, F. D. (2000). A Theoretical Extension of the Technology Acceptance Model: Four longitudinal Field Studies. Management Science, 46(2), 186-204.
  60. Venkatesh, V., Morris, M. G., & Ackerman, P. L. (2000). A Longitudinal Field Investigation of Gender Differences in Individual Technology Adoption Decision-Making Processes. Organizational Behavior and Human Decision Processes, 83(1), 33-60. doi:10.1006/obhd.2000.2896
  61. Venkatesh, V., Morris, M. G., Davis, G. B., & Davis, F. D. (2003). User Acceptance of Information Technology: Toward a Unified View. MIS Quarterly, 27(3), 425-478.
  62. Venkatesh, V., Sykes, T. A., & Venkatraman, S. (2014). Understanding E-government Portal Use in Rural India: Role of Demographic and Personality Characteristics. Information Systems Journal, 24, 249-269. doi:10.1111/isj.12008
  63. Warkentin, M., Gefen, D., Pavlou, P., & Rose, G. (2002). Encouraging Citizen Adoption of E-government by Building Trust. Electronic Markets, 12(3), 157-162.

Copyright information

Creative Commons License
This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.

About this article

Publication Date

18 December 2019

eBook ISBN

978-1-80296-039-6

Publisher

Future Academy

Volume

40

Print ISBN (optional)

-

Edition Number

1st Edition

Pages

1-1231

Subjects

Business, innovation, sustainability, environment, green business, environmental issues

Cite this article as:

Chintamanee, S. (2019). E-Government In Mauritius: A Principal Component Analysis. In & M. Imran Qureshi (Ed.), Technology & Society: A Multidisciplinary Pathway for Sustainable Development, vol 40. European Proceedings of Social and Behavioural Sciences (pp. 1019-1035). Future Academy. https://doi.org/10.15405/epsbs.2018.05.82