Preprint
Article

Design and Validation of an Instrument to Measure E-governance through Factor Analysis

Altmetrics

Downloads

90

Views

58

Comments

0

A peer-reviewed article of this preprint also exists.

Submitted:

29 April 2024

Posted:

01 May 2024

You are already at the latest version

Alerts
Abstract
(1) E-governance is defined as the application of electronic means in the interaction between government and citizens and government and business, as well as in internal government operations to simplify and improve democratic, governmental, and business aspects of governance. Thus, e-governance is built from a paradigmatic dimension such as e-democracy (relationship between government and citizens) and an operational one such as e-government. The objective was to design and validate an instrument to measure e-governance based on three factors: a) e-administration, b) e-services, and c) e-democracy; (2) Methods: Based on the level of importance given to each factor (sample of 2042 Latin American citizens), as well as the relationships between them, an analysis of the importance of each factor is carried out; (3) Results: After the confirmatory analysis, the definitive instrument with which e-governance can be measured by other researchers and future research is obtained, considering the three selection factors, namely: e-administration, e-services and e-democracy; (4) Conclusions: This research contributes to political science through the design and validation of an instrument consisting of 39 items that can be used to measure e-governance according to the dimensions proposed by the United Nations Educational, Scientific and Cultural Organization.
Keywords: 
Subject: Social Sciences  -   Government

1. Introduction

E-governance is not new. In fact, it appeared in the 1930s, but it was limited to the realm of business administration [1]. In the 1990s, the report of the High Level Group of Experts, prepared by the European Unio [2], concluded that "States must be key players in the Knowledge Society, as articulators (institutional and intersectoral) and producers of high-value content" [3].
As a result, e-government would become an ideal model to facilitate knowledge transfer and insertion in a wide range of sectors. E-government has been identified as a mechanism for developing the Knowledge Society in the report [2]. Between the two dimensions of e-government, identifies e-government as one, and e-democracy as the other. The concept of e-governance refers to the use of electronic means in government interactions with citizens and businesses, as well as in internal government operations, to simplify and improve democratic, governmental, and business aspects [4]. An e-governance system derives from a paradigmatic dimension such as e-democracy (relationship between government and citizens) and an operational dimension such as e-government.
But could we say that the research community has applied and validated instruments that allow us to measure e-governance? A search in Scopus in 2013 yields 47 documents using the string "e-governance" AND "measurement". Of these 47 documents, 11 are open access and provide useful results for this research (Table 1):
Since its inception, the experiences of modernizing the State, through e-governance, have promised at least two advances: greater efficiency and better democracy. In the research by [14], it is argued that e-governance could translate into the creation of real and virtual spaces so that citizens can exercise due social control over those in power, and a fundamental step to get there is transparency.
To assess the level of development of e-governance in Latin America, this project uses the three dimensions proposed by [15]:
  • Electronic administration (e-government) – refers to the improvement of government and public sector officials' processes through new ICT processes.
  • Electronic services (e-services): refers to improving the ease of providing government services to citizens. Examples of online services include: requests for government documents, requests for legal documents and certificates, licenses, and permits.
  • Electronic democracy (e-democracy): requires an increasingly active participation of people in the decision-making process thanks to IT.

2. Materials and Methods

This is a quantitative research with a cross-sectional design. For the purpose of validating the "Electronic Governance" questionnaire (Table 3), an exploratory factor analysis was used, followed by confirmatory factor analysis. Factor analysis is a technique used to reduce a large number of variables to a smaller number of factors. This method extracts the maximum common variance from all variables and combines them into a total score. Factor analysis is part of the General Linear Model (GLM), and this method also makes some assumptions: there is a linear relationship, there is no multicollinearity, the relevant variables are included in the analysis, and they have real correlations between variables and factors [16].
For the purposes of this study, the principal component analysis (PCA) method was used, which is the most commonly used by the researchers. The ACP starts by extracting the maximum variance and factoring it in first. It then removes the variance explained by the first factor and begins to extract the maximum variance for the second factor. The process boils down to this last element [16].
As this is a regional study, the main intention of the study was to apply the instrument in as many cities and regions as possible in Latin America. Of course, the limitation was the access that the researchers of this project were able to have to the people. The population consisted of 21,721,761 adults from Venezuela (Zulia state), Mexico (Nuevo León Department), Argentina (Tucumán, Salta, Misiones, Santa Cruz, Córdoba), Perú (La Libertad Department), Cuba (Habana) and Colombia (Boyacá Department). A sample of 2042 people was calculated, with a margin of error of 3% and 99% reliability. A quota sampling was designed, distributing the subjects as follows (Table 2):
Table 2. Sample.
Table 2. Sample.
Countries Regions Population % p Sample
Venezuela Zulia 5126000 23,6 0,236 481,91
México Nuevo León 5784442 26,63 0,2663 543,78
Argentina Tucumán, salta, misiones, santa cruz, Córdoba 4129480 19,01 0,19 387,98
Perú La Libertad 1778000 8,185 0,08185 167,14
Cuba La Habana 3686839 16,97 0,1697 346,53
Colombia Boyacá 1217000 5,603 0,05603 114,41
TOTAL 21721761 100 0,99988 2041,8
Table 3. Instrument for measuring e-governance.
Table 3. Instrument for measuring e-governance.
Factor # Item
e-administration 1 The technological infrastructure (home or mobile internet, Wi-Fi zones) should be private.
2 The technological infrastructure (home or mobile internet, Wi-Fi zones) should be public.
3 The local (Municipal) government adequately manages ICT (Information and Communication Technologies) platforms to respond to citizens' needs.
4 The regional government (State, Department, Province) adequately manages ICT (Information and Communication Technologies) platforms to respond to the needs of citizens.
5 The national government adequately manages ICT (Information and Communication Technologies) platforms to respond to citizens' needs.
6 The parliament (Congress, National Assembly) adequately manages ICT (Information and Communication Technologies) platforms to respond to citizens' needs.
e-services 7 The local (Municipal) government should have a functional website to report on its management.
8 The regional government (State, Department, Province) should have a functional website to report on its management.
9 The national government (Presidency) should have a functional website to report on its management.
10 The parliament (Congress, National Assembly) should have a functional website to report on its management.
11 The local (municipal) government should have an interactive website where citizens' requests are answered.
12 The regional government (State, Department, Province) should have an interactive website where citizens' requests are answered.
13 The national government (Presidency) should have an interactive website where citizens' requests are answered.
14 The local (Municipal) government should use its website to carry out procedures without the citizen having to physically go to the offices.
15 The regional government (State, Department, Province) should use its website to carry out procedures without the citizen having to physically go to the offices.
16 The national government (Presidency) should use its website to carry out procedures without the citizen having to physically go to the offices.
17 The parliament (Congress, National Assembly) should use its website to carry out procedures without the citizen having to physically go to the offices.
18 The local (Municipal) government should use its website to account for the resources it manages.
19 The regional government (State, Department, Province) should use its website to account for the resources it administers.
20 The national government (Presidency) should use its website to account for the resources it administers.
21 The local (Municipal) government should have a user-friendly website where information is easily found (navigability).
22 The regional government (State, Department, Province) should have a user-friendly website where information can be easily found (navigability).
23 The national government (Presidency) should have a user-friendly website where information can be easily found (navigability).
24 The parliament (Congress, National Assembly) should have a user-friendly website where information can be easily found (navigability).
25 The local (Municipal) government should have a website with aids and options for people with functional diversity or disability (accessibility).
26 The national government (Presidency) should have a website with aids and options for people with functional diversity or disability (accessibility).
27 The parliament (Congress, National Assembly) should have a website with aids and options for people with functional diversity or disability (accessibility).
e-democracy 28 The local government (Mayor's Office) should use digital media (website, social networks) to consult citizens on the effectiveness of its management through surveys or other instruments.
29 The regional government (State-Department) should use digital media (website, social networks) to consult citizens on the effectiveness of its management through surveys or other instruments.
30 The national government (Presidency) should use digital media (website, social networks) to consult citizens on the effectiveness of its management through surveys or other instruments.
31 The parliament (Congress, National Assembly) should use digital media (website, social networks) to consult citizens on the effectiveness of its management through surveys or other instruments.
32 The local government (Mayor's Office) should use digital media (website, social networks) to directly involve citizens in decision making (electronic voting).
33 The regional government (State-Department) should use digital media (website, social networks) to directly involve citizens in decision making (electronic voting).
34 The national government (Presidency) should use digital media (website, social networks) to directly involve citizens in decision making (electronic voting).
35 The parliament (Congress, National Assembly) should use digital media (website, social networks) to directly involve citizens in decision making (electronic voting).
36 The election of the mayor should take place remotely through electronic voting.
37 The election of the governor should take place remotely through electronic voting.
38 The election of the president should take place remotely through electronic voting.
39 The election of deputies or senators (Congress, National Assembly) should take place remotely through electronic voting.
40 The parliament (Congress, National Assembly) should have an interactive website where citizens' requests are answered.
41 The regional government (State, Department, Province) should have a website with aids and options for people with functional diversity or disability (accessibility).
The null hypothesis of the test is that the variables are orthogonal, that is, they are not correlated. The alternative hypothesis is that the variables are not orthogonal, that is, they are sufficiently correlated that the correlation matrix diverges significantly from the identity matrix.

3. Results

3.1. Exploratory Factor Analysis

In this first phase, an exploratory factor analysis was used, in which it is assumed that any indicator or variable can be associated with any factor. It is the most widely used factor analysis by researchers and is not based on any previous theory.
Several tests are needed to determine the strength of the correlation between the variables. The Kaiser-Meyer-Olkin (KMO) test was used and the result was 0.963, indicating that factor analysis can be performed (Table 1). The Kaiser-Meyer-Olkin (KMO) test determines whether the data is suitable for factor analysis. This test measures the fit of the sample for each variable in the model. This statistic is a measure of the ratio of variance between variables that are likely to share the variation. The lower the ratio, the more suitable the data will be for factor analysis [17].
The KMO returns values between 0 and 1. A general rule of thumb for interpreting the statistic is that:
KMO values between 0.8 and 1 indicate that sampling is adequate. KMO values below 0.6 indicate that sampling is inadequate and corrective action should be taken. Some authors put this value at 0.5, so use your own criteria for values between 0.5 and 0.6. KMO values close to zero mean that there are large partial correlations compared to the sum of correlations. In other words, there are generalized correlations that pose a major problem for factor analysis [17].
Bartlett's sphericity test was also used with a result of 0.00, which also confirmed the factor analysis (Table 4). Bartlett's sphericity test compares the observed correlation matrix with the identity matrix. Basically, it checks for any redundancy between variables that can be summarized with a small number of factors. The null hypothesis of the test is that the variables are orthogonal, i.e., they are not correlated. Another hypothesis is that the variables are not orthogonal, i.e., they are so correlated that the correlation matrix is significantly different from the identity matrix. This test is often performed before applying a data reduction method, such as principal component analysis or factor analysis, to ensure that the data reduction method actually compresses the data in a meaningful [18].
The results were examined in the anti-image correlation matrix as the values were not close to zero (Table 5 and Table 6). The anti-image correlation matrix contains negative values of partial correlation coefficients, while the anti-image covariance matrix contains negative values of partial covariances. In a good coefficient model, most elements outside the diagonal will be small [19]. On the diagonal of the anti-image correlation matrix, a measure of sampling suitability for a variable is shown. As a result of this analysis, it was determined that item 1 (in pink) will be eliminated in the confirmatory analysis because it has a value below 0.700.
In communalities, the values closest to 1 are taken and a minimum value of 0.7 will be obtained; this is the case of Items 5 and 7 to 41 (Table 7). The commonality of the variable ranges from 0 to 1. In general, one way to understand commonality is through the proportion of the total variance found in a particular variable. A variable with no single variance (i.e., a variable whose variance is 100% explained as a result of other variables) has a commonality of 1. A variable whose variance cannot be explained by other variables has a commonality of 0 [20]. As a result of this analysis, it is determined that in the confirmatory analysis, Items 1 and 2 (in pink) will be eliminated for presenting values below 0.500.
In the total variance explained (Table 8), we can see that 73.329% is concentrated in Items 1 to 7. The total variance is the sum of the variance of all the individual principal components. The proportion of variance explained by a principal component is the ratio of the variance of that principal component to the total variance. To find the principal components, we need to add the variances and divide them by the total variance [21].
In the sedimendation (Figure 1), the optimal eigenvalues that explain most of the variance are shown; in this case they are between 1 and 5.
In the matrix of rotated components (Table 9), you can see the items or components with the greatest strength according to each factor. The items grouped in pink are the ones that have the greatest relationship with each other. In this way, the following Items are placed between factors 1 to 6.

3.2. Confirmatory Factor Analysis

To confirm the strength of the correlation between the variables, several tests are required. The Kaiser-Meyer-Olkin (KMO) test was applied, which gave a result of 0.964, which ratifies the factor analysis. Bartlett's sphericity test was also applied, with a result of 0.000, which also confirms the factor analysis (Table 10).
In this second phase of the factor analysis, we see how the commonalities (Table 8) allow us to confirm Items 3 to 41 (Table 11).
In the total variance explained (Table 12), using the extraction method "principal axis factorization", it is evident that, although 6 factors could have been selected because they were closer to 1, our theoretical model is three-factor; It is observed that 65.401% is concentrated in the first three factors.
In sedimentation (Figure 2), the optimal eigenvalues that explain most of the variance are shown; In this case, they are between 1 and 3.
In the matrix of rotated components (Table 13), the extraction method "principal axis factorization" and the rotation method "Oblimin with Kaiser normalization" have been used. You can see the items or components with the greatest strength according to each factor. The items grouped in pink are the ones that have the greatest relationship with each other. In this way, the following Items are placed between factors 1 to 3.

4. Discussion

After the confirmatory analysis, the definitive instrument is obtained with which e-governance can be measured by other researchers and future research, considering the three selection factors, namely: e-administration, e-services and e-democracy (Figure 3, Table 14).

5. Conclusions

This work was based on the assumption that there were little or no applied and validated measurement instruments that considered the three dimensions of e-governance. In this sense, it coincides with the findings of [7] who present a set of e-governance readiness assessment tools as an application prototype; even though it does not propose an instrument or its validation, the modified scheme of levels of commitment could be useful as a 4-stage implementation of the e-participation maturity model, namely: E-Informing, E-Collaborating, E-Consulting, and E-Empowering. For their part, [8] developed a solution to assess the progress of a national e-government program on the Project Management Maturity Model (PMMM) methodological platform. One of the dimensions of e-governance, which is e-services, is measured.
In the case of [10], it is stated that the evaluation tools are dispersed among various sources and there is no systematized framework that supports the analysis and selection of the appropriate tool for specific situations. The paper aims to answer these questions by characterizing the available literature in the context of the measurement, evaluation and monitoring of the EGOV, in order to generate a knowledge base aimed at the creation of a future catalogue of tools and instruments for the evaluation of the EGOV, and to present a conceptual framework for the choice of an appropriate tool from such a catalogue. [13] support the thesis of the need to design and validate instruments to measure e-governance. E-governance is considered an essential indicator of advanced cities, but measuring the effectiveness of e-governance requires further study.
In conclusion, this research contributes to political science through the design and validation of an instrument consisting of 39 Items that can be used to measure e-governance according to the dimensions proposed by [15], namely: 1) e-government: understood as the improvement of government processes and public sector officials through new information technologies; 2) e-services, which refer to improving the delivery of public services; and 3) e-democracy, which implies greater and more active participation of citizens in decision-making processes through the use of information and communication technologies.

Author Contributions

Conceptualization, A.E.P.M.; methodology, C.P.F. and F.R.I.; software, A.E.P.M; validation, C.P.F. and F.R.I.; formal analysis, A.E.P.M.; investigation, F.R.I.; resources, C.P.F.; data curation, A.E.P.M.; writing—original draft preparation, A.E.P.M., C.P.F. and F.R.I.; writing—review and editing, F.R.I.; visualization, A.E.P.M.; supervision, C.P.F.; project administration, C.P.F. All authors have read and agreed to the published version of the manuscript.

Funding

This research received funding from Universidad de Boyacá.

Institutional Review Board Statement

Not applicable.

Informed Consent Statement

The participants were informed and accepted the following statement: I understand that my participation is completely voluntary, that I can withdraw from the study whenever I want without having to give explanations and that this will not affect my medical care. I freely give my consent to participate in the Research Project entitled "E-governance in Latin America".

Data Availability Statement

The original contributions presented in the study are included in the article/supplementary material, further inquiries can be directed to the corresponding author/s.

Conflicts of Interest

The authors declare no conflicts of interest.

References

  1. Abdel-Rahman, T. E-governance and University of Ha'il institutional excellence in light of the Kingdom's Vision 2030: An Empirical Study on Faculty Member Staff. International Journal of Future Generation Communication and Networking, 2021, 14(1), 462-473. [CrossRef]
  2. Grupo de Expertos de Alto Nivel (GEAN). La construcción de la sociedad europea de la información: Informe final. 1997. http://europa.eu.
  3. Kaufman, E., & Piana, R. S. Algunas aclaraciones sobre gobierno electrónico y sociedad de la información y el conocimiento. En Políticas públicas y tecnologías: Líneas de acción para América Latina. 2007. Primera Edición, Buenos Aires, Argentina, La Crujía Ediciones.
  4. Backus, M. E-Governance and Developing Countries. 2001 https://bibalex.org/baifa/Attachment/Documents/119334.pdf.
  5. Afrizal, Y. The Arrangement of the Information Technology and Communications Master Plan using PeGI Model (e-Governance Ranking Indonesia) to Improve District Government Services. In IOP Conference Series: Materials Science and Engineering. 2018, 407. 012141. [CrossRef]
  6. Khamparia, A & Pandey, B . A QoS and Cognitive Parameters based Uncertainty Model for Selection of Semantic Web Services. Indian Journal of Science and Technology, 2016, 9(44), 1-7. [CrossRef]
  7. Waseem, A. A., Ahmed Shaikh, Z., & ur Rehman, A. A toolkit for prototype implementation of E-Governance service system readiness assessment framework. En F. H. Nah & C. H. Tan (Eds.), HCI in Business, Government, and Organizations: Information Systems, 2016, 9752, 259-270. Springer, Cham. [CrossRef]
  8. Fesenko, T., & Fesenko, G. E-readiness evaluation modelling for monitoring the national e-government programme (by the example of Ukraine). Вoстoчнo-Еврoпейский журнал передoвых технoлoгий, 2016, 3 (3), 28-35. [CrossRef]
  9. Meyerhoff Nielsen, M. Georgia on my mind: A study of the role of governance and cooperation in online service delivery in the Caucasus, In International Conference on Electronic Government, 2017, 71-91. Cham: Springer International Publishing. [CrossRef]
  10. Carvalho, J., & Soares, D. Who Is Measuring What and How in EGOV Domain?. In Electronic Government: 17th IFIP WG 8.5 International Conference, EGOV 2018, Krems, Austria, September 3-5, 2018, Proceedings 17, 20-131. Springer International Publishing. [CrossRef]
  11. Lubis, Muharman & Lubis, Arif & Almaarif, Ahmad & Fajrillah, Asti Amalia. Relationship of Personal Data Protection towards the Electoral Measures: Partial Least Square Analysis. In Journal of Physics: Conference Series, 2020, 1566(1), 012111. [CrossRef]
  12. Abouddaka, I., Bassiri, M., Atibi, A., Tridane, M., & Belaaouad, S. The Engineering of E-governance and Technology in the Management of Secondary Schools: Case of the Nouaceur Delegation. Journal of Information Technology Management, 13(Special Issue: Advanced Innovation Topics in Business and Management), 2021, 229-237. [CrossRef]
  13. Wang Y., Sun B., & Shi H. Mapping the e-governance efficiency of Chinese cities. Regional Studies, Regional Science, 2023, 10(1), 676-678. [CrossRef]
  14. Páez, A., Montoya, J. y Matheus, S. Transparencia web en el gobierno digital de las Américas. En Acevedo, A., Chamorro, A. y Quintero, M. Comunicación política en la esfera pública digital: Representaciones, poder y subjevitidades. Barranquilla: Universidad de la Costa. 2022. https://hdl.handle.net/11323/9592.
  15. Organización de las Naciones Unidas para la Educación, la Ciencia y la Cultura [UNESCO]. Gobernabilidad electrónica. Fortalecimiento de capacidades de la gobernabilidad electrónica. 2022. http://148.202.167.116:8080/jspui/bitstream/123456789/597/1/Gobernabilidad%20electr%C3%B3nica.%20fortalecimiento%20de%20capacidades%20de%20la%20gobernabilidad%20electr%C3%B3nica.pdf.
  16. UCLA: Statistical Consulting Group. Introduction to SAS. 2021. https://stats.oarc.ucla.edu/sas/modules/introduction-to-the-features-of-sas.
  17. Costales, J., Catulay, J., Costales, J., & Bermudez, N. Kaiser-Meyer-Olkin Factor Analysis: A Quantitative Approach on Mobile Gaming Addiction using Random Forest Classifier. In Proceedings of the 6th International Conference on Information System and Data Mining, 2022, 18-24. [CrossRef]
  18. Thao, N. T. P., Van Tan, N., & Tuyet, M. T. A. KMO and Bartlett's Test for Components of Workers' Working Motivation and Loyalty at Enterprises in Dong Nai Province of Vietnam. International Transaction Journal of Engineering, Management, & Applied Sciences & Technologies, 2022, 13(10), 1-13. [CrossRef]
  19. Wu, X., & Huang, X. Screening of urban environmental vulnerability indicators based on coefficient of variation and anti-image correlation matrix method. Ecological Indicators, 2023, 150, 110196. [CrossRef]
  20. Lee, S. Exploratory Factor Analysis for a Nursing Workaround Instrument in Korean and Interpretations of Statistical Decision Points. Computers, informatics, nursing: CIN, 2021, 39(6), 329–339. [CrossRef]
  21. Shrestha, N. Factor Analysis as a Tool for Survey Analysis. American Journal of Applied Mathematics and Statistics, 2021, 9(1), 4-11. [CrossRef]
Figure 1. Sedimentation.
Figure 1. Sedimentation.
Preprints 105205 g001
Figure 2. Sedimentation.
Figure 2. Sedimentation.
Preprints 105205 g002
Figure 3. E-governance factors.
Figure 3. E-governance factors.
Preprints 105205 g003
Table 1. Findings on e-governance measurement.
Table 1. Findings on e-governance measurement.
# Year Works´s title Findings Proposes and validates an instrument for measuring e-governance
1 2013 E-governance in Lithuanian Municipalities: External Factors Analysis of the Websites Development [5]. The paper focuses on the usability of public organizations' websites, as well as on the external factors influencing the development of Lithuanian municipal websites. It measures one of the dimensions of e-governance which is e-services. Parcial
2 2016 A QoS and Cognitive Parameters based Uncertainty Model for Selection of Semantic Web Services [6]. The main objective of this research work is to present a model based on cognitive and quality of service parameters for the selection of semantic web services. An e-governance tool is not proposed or validated. No
3 2016 A Toolkit for Prototype Implementation of E-Governance Service System Readiness Assessment Framework [7]. This research paper presents a set of e-governance readiness assessment tools as a prototype application. Although it does not propose an instrument or its validation, the modified Levels of Engagement scheme could be useful as a 4-stage implementation of the e-participation maturity model, namely
e-participation maturity model, namely: E-Informing, E-Collaborating, E-Consulting, and E-Empowering.
Parcial
4 2016 E-readiness evaluation modelling for monitoring the national e-government programme [8]. The study aims to develop a solution to assess the progress of a national e-government program on the methodological platform of the Project Management Maturity Model (PMMM). It measures one of the dimensions of e-governance which is e-services. The study concludes that it is necessary to assess the dynamics of the "e-Ukraine" program by introducing weighting coefficients for e-governance indices and sub-indices. Partial
5 2017 Georgia on my mind: a study of the role of governance and cooperation in online service delivery in the Caucasus [9]. E-services indicators are proposed, although the instrument is not validated. The analysis highlights the influence of politically driven public sector reforms supported by the use of ICTs to improve service delivery, transparency and anti-corruption in the period 2004-2012. The article concludes that eGovernment is fragmented and that the use of public and private online services (eService) is limited, despite the high penetration and use of the Internet. Parcial
6 2018 The Arrangement of the Information Technology and Communications Master Plan using PeGI Model (e-Governance Ranking Indonesia) to Improve District Government Services [5]. E-services indicators are proposed, although the instrument is not validated. The information and communication technology master plan for local government is a product of scientific research with the PeGI (Indonesian e-Government ranking) model as a measurement model of the e-Government system. The PeGI model takes measures in 5 (five) dimensions of e-Government system: policy, institutional,
infrastructure, implementation and planning.
Partial
7 2018 Who Is Measuring What and How in EGOV Domain? [10]. This is a literature review. It does not validate an instrument, although it makes contributions by stating that assessment tools are scattered among various sources and that there is no systematized framework to support the analysis and selection of the appropriate tool for specific situations. The paper aims to answer these questions by characterizing the available literature in the context of EGOV measurement, evaluation and monitoring, with the aim of generating a
knowledge base oriented towards the creation of a future catalog of tools and instruments for EGOV assessment, and to present a conceptual framework for the choice of an appropriate tool from such a catalog.
Partial
8 2020 Relationship of Personal Data Protection towards the Electoral Measures: Partial Least Square Analysis [11]. The study addresses one of the indicators of the e-democracy dimension, namely e-voting. The adoption of e-voting in several countries poses certain challenges, which are very similar when applying electronic means to any activity, such as e-governance or e-commerce. Therefore, some people, for economic, political or social reasons, expect that the use of e-voting will facilitate and solve election problems.
Unfortunately, the practical implementation is more complex and difficult, with different problems and depends on the conditions or culture of each country or culture. One of the essential factors for adoption is related to privacy protection. Thus, this study examines the relationship between perceived benefits and concern for personal data protection by establishing a formative measurement model.
Partial
9 2021 E-governance and University of Ha'il institutional excellence in light of the Kingdom's Vision 2030: An Empirical Study on Faculty Member [1]. The objective of this research is to identify the impact of e-governance on institutional excellence at the University of Ha'il. The following dimensions are proposed and validated to measure e-governance: Transparency, Accountability, Participation, Level of e-services provided, Change management and Infrastructure. Si
10 2021 The Engineering of E-governance and Technology in the Management of Secondary Schools: Case of the Nouaceur Delegation [12]. The objective of this study is to measure the impact of governance on the organizational performance of schools in administrative, financial and pedagogical aspects. Although the instrument is not validated, several principles are proposed to measure e-governance, such as: participation, transparency, accountability and evaluation. Partial
11 2023 Mapping the e-governance efficiency of Chinese cities [13] The article supports the thesis of the need to design and validate instruments to measure e-governance. E-governance is considered an essential indicator of advanced cities, but the measurement of e-governance efficiency requires further study. Following this line of research, this article proposes an e-governance efficiency index (GEI) that is applied to Chinese cities. Si
Table 4. KMO and Bartlett Test.
Table 4. KMO and Bartlett Test.
Kaiser-Meyer-Olkin measure of sampling adequacy of sampling adequacy ,963
Bartlett's test for sphericity Aprox. Chi-cuadrado 93297,391
gl 820
Sig. ,000
Table 5. Anti-image matrices (Items 1 to 20).
Table 5. Anti-image matrices (Items 1 to 20).
Item1 Item2 Item3 Item4 Item5 Item6 Item7 Item8 Item9 Item10 Item11 Item12 Item13 Item14 Item15 Item16 Item17 Item18 Item19 Item20
Correlación anti-imagen Item1 ,574a ,466 -,120 -,028 ,026 -,071 -,068 ,011 -,017 ,020 -,006 -,018 ,027 -,003 ,026 ,006 -,040 -,009 ,014 ,004
Item2 ,466 ,700a -,067 -,013 -,068 -,054 -,024 ,004 -,017 -,002 ,033 -,015 -,001 ,012 ,044 -,002 -,047 -,028 ,019 -,017
Item3 -,120 -,067 ,819a -,524 -,085 -,162 -,021 ,036 -,018 ,040 -,064 -,020 ,053 ,003 ,014 ,012 -,036 ,103 -,024 -,044
Item4 -,028 -,013 -,524 ,814a -,285 -,128 ,040 -,035 ,027 -,061 ,027 ,025 -,047 -,030 -,011 -,004 ,050 -,049 ,029 ,014
Item5 ,026 -,068 -,085 -,285 ,819a -,556 -,054 ,058 -,014 -,021 -,006 ,059 -,029 -,004 -,040 -8,211E-5 ,046 -,058 ,015 ,047
Item6 -,071 -,054 -,162 -,128 -,556 ,833a ,033 -,059 -,012 ,030 ,027 -,044 ,015 ,034 ,015 -,010 -,044 ,023 ,003 -,017
Item7 -,068 -,024 -,021 ,040 -,054 ,033 ,968a -,451 -,158 -,043 -,059 ,004 -,081 -,011 ,047 -,098 ,043 -,019 -,001 ,013
Item8 ,011 ,004 ,036 -,035 ,058 -,059 -,451 ,967a -,202 -,200 -,118 -,016 ,010 ,031 -,052 ,050 -,026 ,030 -,045 ,010
Item9 -,017 -,017 -,018 ,027 -,014 -,012 -,158 -,202 ,976a -,369 ,003 -,015 -,091 -,090 ,024 -,030 ,055 ,014 -,026 -,013
Item10 ,020 -,002 ,040 -,061 -,021 ,030 -,043 -,200 -,369 ,976a -,072 -,064 ,044 ,007 -,023 ,127 -,092 -,002 ,004 -,020
Item11 -,006 ,033 -,064 ,027 -,006 ,027 -,059 -,118 ,003 -,072 ,977a -,361 -,199 -,042 -,056 ,000 ,108 -,096 ,047 ,028
Item12 -,018 -,015 -,020 ,025 ,059 -,044 ,004 -,016 -,015 -,064 -,361 ,975a -,241 -,004 -,063 -,008 ,030 ,065 -,056 ,021
Item13 ,027 -,001 ,053 -,047 -,029 ,015 -,081 ,010 -,091 ,044 -,199 -,241 ,981a -,019 ,042 -,069 ,002 -,056 ,026 ,000
Item14 -,003 ,012 ,003 -,030 -,004 ,034 -,011 ,031 -,090 ,007 -,042 -,004 -,019 ,975a -,380 -,115 -,151 ,028 ,049 -,077
Item15 ,026 ,044 ,014 -,011 -,040 ,015 ,047 -,052 ,024 -,023 -,056 -,063 ,042 -,380 ,965a -,349 -,206 -,051 -,092 ,062
Item16 ,006 -,002 ,012 -,004 -8,211E-5 -,010 -,098 ,050 -,030 ,127 ,000 -,008 -,069 -,115 -,349 ,966a -,383 ,036 ,033 -,063
Item17 -,040 -,047 -,036 ,050 ,046 -,044 ,043 -,026 ,055 -,092 ,108 ,030 ,002 -,151 -,206 -,383 ,971a -,088 -,020 ,052
Item18 -,009 -,028 ,103 -,049 -,058 ,023 -,019 ,030 ,014 -,002 -,096 ,065 -,056 ,028 -,051 ,036 -,088 ,972a -,412 -,193
Item19 ,014 ,019 -,024 ,029 ,015 ,003 -,001 -,045 -,026 ,004 ,047 -,056 ,026 ,049 -,092 ,033 -,020 -,412 ,949a -,579
Item20 ,004 -,017 -,044 ,014 ,047 -,017 ,013 ,010 -,013 -,020 ,028 ,021 ,000 -,077 ,062 -,063 ,052 -,193 -,579 ,958a
Source: own elaboration.
Table 6. Matrices anti-imagen (Items 21 al 41).
Table 6. Matrices anti-imagen (Items 21 al 41).
Item21 Item22 Item23 Item24 Item25 Item26 Item27 Item28 Item29 Item30 Item31 Item32 Item33 Item34 Item35 Item36 Item37 Item38 Item39 Item40 Item41
Correlación anti-imagen Item21 ,982a -,374 -,155 -,086 -,027 -,050 ,008 -,024 ,034 -,029 -,014 ,072 -,044 ,029 -,053 ,003 -,019 -,003 ,031 -,001 -,033
Item22 -,374 ,977a -,262 -,143 -,034 -,008 -,004 ,057 -,047 -,022 ,016 -,012 ,045 -,019 -,016 -,055 ,002 -,031 ,086 -,026 ,008
Item23 -,155 -,262 ,976a -,370 -,038 ,018 -,040 ,029 -,049 ,037 -,059 ,008 -,063 -,019 ,101 ,062 -,023 ,000 -,038 ,036 -,096
Item24 -,086 -,143 -,370 ,981a -,132 -,033 -,070 -,021 ,018 ,067 -,060 -,013 ,061 -,034 -,012 ,018 -,009 ,004 -,025 -,007 -,009
Item25 -,027 -,034 -,038 -,132 ,981a -,262 -,213 -,028 ,008 -,007 ,005 ,012 -,084 ,094 ,004 -,060 -,027 ,043 ,045 ,031 -,203
Item26 -,050 -,008 ,018 -,033 -,262 ,976a -,312 -,054 -,039 ,030 ,036 ,039 ,005 -,013 -,052 ,077 -,059 ,060 -,052 -,055 -,271
Item27 ,008 -,004 -,040 -,070 -,213 -,312 ,982a -,020 ,006 -,077 ,060 -,043 ,001 -,033 ,078 -,007 ,041 -,021 -,026 -,040 -,155
Item28 -,024 ,057 ,029 -,021 -,028 -,054 -,020 ,968a -,412 -,211 -,085 -,051 ,069 -,066 ,020 -,026 ,073 -,052 -,006 ,050 ,057
Item29 ,034 -,047 -,049 ,018 ,008 -,039 ,006 -,412 ,961a -,286 -,262 ,027 -,023 -,015 -,001 ,042 -,088 ,052 ,002 -,003 -,032
Item30 -,029 -,022 ,037 ,067 -,007 ,030 -,077 -,211 -,286 ,960a -,419 -,036 -,015 ,041 -,045 -,012 ,010 ,024 -,014 -,067 -,022
Item31 -,014 ,016 -,059 -,060 ,005 ,036 ,060 -,085 -,262 -,419 ,968a -,042 -,047 ,047 -,028 -,040 ,043 -,043 ,036 -,034 -,049
Item32 ,072 -,012 ,008 -,013 ,012 ,039 -,043 -,051 ,027 -,036 -,042 ,958a -,414 -,243 -,142 -,032 -,015 ,036 -,004 ,052 -,024
Item33 -,044 ,045 -,063 ,061 -,084 ,005 ,001 ,069 -,023 -,015 -,047 -,414 ,940a -,392 -,233 -,020 -,018 ,055 -,032 ,014 ,079
Item34 ,029 -,019 -,019 -,034 ,094 -,013 -,033 -,066 -,015 ,041 ,047 -,243 -,392 ,942a -,354 ,004 ,002 -,121 ,070 -,081 -,049
Item35 -,053 -,016 ,101 -,012 ,004 -,052 ,078 ,020 -,001 -,045 -,028 -,142 -,233 -,354 ,963a -,028 -,001 ,026 -,061 ,039 -,018
Item36 ,003 -,055 ,062 ,018 -,060 ,077 -,007 -,026 ,042 -,012 -,040 -,032 -,020 ,004 -,028 ,921a -,482 -,111 -,240 ,015 -,032
Item37 -,019 ,002 -,023 -,009 -,027 -,059 ,041 ,073 -,088 ,010 ,043 -,015 -,018 ,002 -,001 -,482 ,891a -,389 -,255 ,001 ,067
Item38 -,003 -,031 ,000 ,004 ,043 ,060 -,021 -,052 ,052 ,024 -,043 ,036 ,055 -,121 ,026 -,111 -,389 ,912a -,398 -,001 -,034
Item39 ,031 ,086 -,038 -,025 ,045 -,052 -,026 -,006 ,002 -,014 ,036 -,004 -,032 ,070 -,061 -,240 -,255 -,398 ,923a ,001 -,011
Item40 -,001 -,026 ,036 -,007 ,031 -,055 -,040 ,050 -,003 -,067 -,034 ,052 ,014 -,081 ,039 ,015 ,001 -,001 ,001 ,982a -,011
Item41 -,033 ,008 -,096 -,009 -,203 -,271 -,155 ,057 -,032 -,022 -,049 -,024 ,079 -,049 -,018 -,032 ,067 -,034 -,011 -,011 ,982a
Table 7. Communalities.
Table 7. Communalities.
Item Initial Extraction
Item1 ,264 ,035
Item2 ,284 ,074
Item3 ,642 ,645
Item4 ,689 ,719
Item5 ,706 ,762
Item6 ,682 ,731
Item7 ,718 ,686
Item8 ,786 ,770
Item9 ,748 ,741
Item10 ,766 ,755
Item11 ,781 ,758
Item12 ,796 ,756
Item13 ,791 ,764
Item14 ,736 ,581
Item15 ,784 ,582
Item16 ,775 ,572
Item17 ,759 ,587
Item18 ,750 ,771
Item19 ,831 ,903
Item20 ,792 ,831
Item21 ,757 ,709
Item22 ,784 ,726
Item23 ,814 ,771
Item24 ,785 ,760
Item25 ,801 ,803
Item26 ,814 ,790
Item27 ,793 ,781
Item28 ,744 ,760
Item29 ,808 ,844
Item30 ,798 ,834
Item31 ,770 ,796
Item32 ,805 ,835
Item33 ,847 ,891
Item34 ,839 ,869
Item35 ,778 ,800
Item36 ,856 ,876
Item37 ,894 ,926
Item38 ,860 ,882
Item39 ,855 ,877
Item40 ,768 ,737
Item41 ,783 ,775
Extraction method: maximum likelihood.
Table 8. Total variance explained.
Table 8. Total variance explained.
Factor Initial eigenvalues Sums of squared extraction charges Sums of loads squared by rotation
Total % of variance % accumulated Total % of variance % accumulated Total % of variance % accumulated
1 18,582 45,323 45,323 17,864 43,572 43,572 15,154 36,961 36,961
2 5,193 12,666 57,989 5,246 12,794 56,366 3,679 8,974 45,935
3 2,826 6,893 64,881 2,012 4,908 61,274 3,488 8,507 54,443
4 1,674 4,084 68,965 2,175 5,305 66,579 2,992 7,297 61,739
5 1,412 3,444 72,409 1,018 2,484 69,063 2,438 5,945 67,685
6 1,243 3,032 75,441 ,980 2,391 71,454 1,417 3,455 71,140
7 1,126 2,745 78,186 ,769 1,874 73,329 ,897 2,189 73,329
8 ,969 2,364 80,550
9 ,938 2,287 82,837
10 ,609 1,485 84,321
11 ,502 1,224 85,545
12 ,467 1,138 86,683
13 ,421 1,026 87,709
14 ,349 ,852 88,561
15 ,297 ,723 89,285
16 ,268 ,655 89,939
17 ,265 ,647 90,586
18 ,262 ,639 91,225
19 ,249 ,607 91,832
20 ,238 ,580 92,412
21 ,219 ,534 92,946
22 ,201 ,489 93,436
23 ,193 ,471 93,906
24 ,191 ,465 94,372
25 ,186 ,452 94,824
26 ,174 ,425 95,249
27 ,169 ,412 95,661
28 ,162 ,394 96,055
29 ,156 ,381 96,436
30 ,151 ,368 96,804
31 ,147 ,358 97,163
32 ,145 ,353 97,515
33 ,137 ,334 97,849
34 ,131 ,319 98,168
35 ,128 ,312 98,480
36 ,124 ,301 98,781
37 ,120 ,294 99,075
38 ,107 ,260 99,335
39 ,104 ,255 99,590
40 ,095 ,231 99,821
41 ,074 ,179 100,000
Método de extracción: máxima verosimilitud.
Table 9. Rotated Component Matrix.
Table 9. Rotated Component Matrix.
Item Factor
1 2 3 4 5 6 7
Item25 ,863
Item26 ,854
Item27 ,848
Item41 ,846
Item24 ,841
Item23 ,841
Item13 ,821
Item12 ,820
Item22 ,816
Item11 ,814
Item40 ,805
Item21 ,803
Item10 ,780
Item8 ,767
Item9 ,750
Item14 ,720
Item7 ,717
Item16 ,715
Item17 ,713
Item15 ,710
Item18 ,621 ,570
Item37 ,918
Item38 ,898
Item39 ,893
Item36 ,884
Item33 ,848
Item34 ,828
Item32 ,810
Item35 ,785
Item5 ,860
Item4 ,842
Item6 ,842
Item3 ,796
Item2
Item1
Item30 ,514 ,705
Item29 ,541 ,697
Item31 ,513 ,675
Item28 ,508 ,653
Item19 ,631 ,668
Item20 ,617 ,629
Extraction method: maximum likelihood.
Rotation method: Varimax with Kaiser normalization.
a. The rotation has converged in 6 iterations.
Table 10. KMO and Bartlett Test.
Table 10. KMO and Bartlett Test.
Kaiser-Meyer-Olkin measure of sampling adequacy ,964
Bartlett's test for sphericity Approx. chi-square 92522,546
gl 741
Sig. ,000
Table 11. Communalities.
Table 11. Communalities.
Item Initial Extraction
Item3 ,636 ,625
Item4 ,688 ,711
Item5 ,703 ,726
Item6 ,680 ,690
Item7 ,717 ,571
Item8 ,786 ,654
Item9 ,748 ,637
Item10 ,766 ,670
Item11 ,780 ,689
Item12 ,796 ,702
Item13 ,791 ,718
Item14 ,736 ,597
Item15 ,783 ,589
Item16 ,775 ,582
Item17 ,759 ,594
Item18 ,749 ,560
Item19 ,831 ,585
Item20 ,792 ,551
Item21 ,756 ,681
Item22 ,784 ,692
Item23 ,814 ,721
Item24 ,785 ,705
Item25 ,801 ,720
Item26 ,814 ,717
Item27 ,793 ,713
Item28 ,744 ,528
Item29 ,807 ,573
Item30 ,797 ,550
Item31 ,770 ,542
Item32 ,805 ,643
Item33 ,847 ,668
Item34 ,839 ,678
Item35 ,778 ,649
Item36 ,856 ,728
Item37 ,894 ,730
Item38 ,860 ,694
Item39 ,855 ,701
Item40 ,768 ,709
Item41 ,783 ,711
Método de extracción: factorización de eje principal.
Table 12. Total variance explained.
Table 12. Total variance explained.
Factor Initial eigenvalues Sums of squared extraction charges Sums of loads squared by rotation
Total % of variance % accumulated Total % of variance % accumulated Total
1 18,570 47,617 47,617 18,218 46,713 46,713 17,948
2 5,135 13,167 60,783 4,830 12,384 59,096 7,408
3 2,776 7,119 67,902 2,459 6,305 65,401 3,393
4 1,668 4,277 72,179
5 1,259 3,229 75,409
6 1,127 2,891 78,300
7 ,972 2,492 80,792
8 ,938 2,405 83,197
9 ,609 1,561 84,757
10 ,467 1,196 85,954
11 ,427 1,096 87,049
12 ,350 ,899 87,948
13 ,298 ,765 88,713
14 ,270 ,693 89,406
15 ,266 ,682 90,088
16 ,262 ,672 90,760
17 ,250 ,641 91,401
18 ,238 ,611 92,013
19 ,219 ,563 92,575
20 ,201 ,515 93,090
21 ,194 ,497 93,587
22 ,191 ,490 94,077
23 ,186 ,477 94,554
24 ,174 ,447 95,000
25 ,169 ,434 95,434
26 ,162 ,414 95,849
27 ,156 ,401 96,250
28 ,151 ,387 96,637
29 ,147 ,377 97,014
30 ,145 ,371 97,385
31 ,137 ,352 97,737
32 ,131 ,336 98,073
33 ,128 ,328 98,401
34 ,124 ,317 98,718
35 ,121 ,309 99,027
36 ,107 ,274 99,300
37 ,105 ,268 99,568
38 ,095 ,243 99,811
39 ,074 ,189 100,000
Extraction method: principal axis factorization.
a. When factors are correlated, the sums of the squared loadings cannot be added to obtain a total variance.
Table 13. Rotated Factor Matrix.
Table 13. Rotated Factor Matrix.
Item Factores
1 2 3
Item13 ,868
Item40 ,863
Item12 ,863
Item25 ,862
Item11 ,858
Item23 ,856
Item26 ,854
Item27 ,853
Item24 ,848
Item41 ,847
Item10 ,846
Item22 ,839
Item8 ,839
Item21 ,831
Item9 ,824
Item7 ,785
Item14 ,769
Item15 ,758
Item16 ,757
Item17 ,752
Item19 ,709
Item18 ,702
Item20 ,691
Item29 ,660
Item30 ,639
Item28 ,630
Item31 ,625
Item36 ,849
Item37 ,844
Item39 ,827
Item38 ,825
Item34 ,737
Item35 ,731
Item33 ,726
Item32 ,708
Item4 ,848
Item5 ,844
Item6 ,822
Item3 ,793
Método de extracción: factorización de eje principal.

Rotation method: Oblimin with Kaiser normalization.
a. The rotation has converged in 5 iterations.
Table 14. Definitive instrument.
Table 14. Definitive instrument.
Factor # Item
e-administration 3 The local (Municipal) government adequately manages ICT (Information and Communication Technologies) platforms to respond to citizens' needs.
4 The regional government (State, Department, Province) adequately manages ICT (Information and Communication Technologies) platforms to respond to citizens' needs.
5 The national government adequately manages ICT (Information and Communication Technologies) platforms to respond to citizens' needs.
6 The parliament (Congress, National Assembly) adequately manages ICT (Information and Communication Technologies) platforms to respond to citizens' needs.
e-services 7 The local (Municipal) government should have a functional website to report on its management.
8 The regional government (State, Department, Province) should have a functional website to report on its management.
9 The national government (Presidency) should have a functional website to report on its management.
10 The parliament (Congress, National Assembly) should have a functional website to report on its management.
11 The local (Municipal) government should have an interactive website where citizens' requests are answered.
12 The regional government (State, Department, Province) should have an interactive website where citizens' requests are answered.
13 The national government (Presidency) should have an interactive website where citizens' requests are answered.
14 The local (Municipal) government should use its website to carry out procedures without the citizen having to physically go to the offices.
15 The regional government (State, Department, Province) should use its website to carry out procedures without the citizen having to physically go to the offices.
16 The national government (Presidency) should use its website to carry out procedures without the citizen having to physically go to the offices.
17 The parliament (Congress, National Assembly) should use its website to carry out procedures without the citizen having to physically go to the offices.
18 The local (Municipal) government should use its website to account for the resources it manages.
19 The regional government (State, Department, Province) should use its website to account for the resources it administers.
20 The national government (Presidency) should use its website to account for the resources it administers.
21 The local (Municipal) government should have a user-friendly website where information is easily found (navigability).
22 The regional government (State, Department, Province) should have a user-friendly website where information can be easily found (navigability).
23 The national government (Presidency) should have a user-friendly website where information can be easily found (navigability).
24 The parliament (Congress, National Assembly) should have a user-friendly website where information can be easily found (navigability).
25 The local (Municipal) government should have a website with aids and options for people with functional diversity or disability (accessibility).
26 The national government (Presidency) should have a website with aids and options for people with functional diversity or disability (accessibility).
27 The parliament (Congress, National Assembly) should have a website with aids and options for people with functional diversity or disability (accessibility).
e-democracy 28 The local government (Mayor's Office) should use digital media (website, social networks) to consult citizens on the effectiveness of its management through surveys or other instruments.
29 The regional government (State-Department) should use digital media (website, social networks) to consult citizens on the effectiveness of its management through surveys or other instruments.
30 The national government (Presidency) should use digital media (website, social networks) to consult citizens on the effectiveness of its management through surveys or other instruments.
31 The parliament (Congress, National Assembly) should use digital media (website, social networks) to consult citizens on the effectiveness of its management through surveys or other instruments.
32 The local government (Mayor's Office) should use digital media (website, social networks) to directly involve citizens in decision making (electronic voting).
33 The regional government (State-Department) should use digital media (website, social networks) to directly involve citizens in decision making (electronic voting).
34 The national government (Presidency) should use digital media (website, social networks) to directly involve citizens in decision making (electronic voting).
35 The parliament (Congress, National Assembly) should use digital media (website, social networks) to directly involve citizens in decision making (electronic voting).
36 The election of the mayor should take place remotely through electronic voting.
37 The election of the governor should take place remotely through electronic voting.
38 The election of the president should take place remotely through electronic voting.
39 The election of deputies or senators (Congress, National Assembly) should take place remotely through electronic voting.
40 The parliament (Congress, National Assembly) should have an interactive website where citizens' requests are answered.
41 The regional government (State, Department, Province) should have a website with aids and options for people with functional diversity or disability (accessibility).
Disclaimer/Publisher’s Note: The statements, opinions and data contained in all publications are solely those of the individual author(s) and contributor(s) and not of MDPI and/or the editor(s). MDPI and/or the editor(s) disclaim responsibility for any injury to people or property resulting from any ideas, methods, instructions or products referred to in the content.
Copyright: This open access article is published under a Creative Commons CC BY 4.0 license, which permit the free download, distribution, and reuse, provided that the author and preprint are cited in any reuse.
Prerpints.org logo

Preprints.org is a free preprint server supported by MDPI in Basel, Switzerland.

Subscribe

© 2024 MDPI (Basel, Switzerland) unless otherwise stated