Importance

This study seeks to review the information gathered to expose the practical and theoretical support of the existing correlation between (1) the use of technology, the attention, and the improvement of good practices that are successful in other countries, and (2) the process quality (certified lines, application of quality models) in order to improve the identity registration service.

Background

For this study, previous works on the subject were reviewed, in which the variables “process quality”, “technology” and their incidence on “service improvement” were studied.

In his doctoral thesis, Sistemas y tecnologías de información y comunicaciones en el proceso de dirección de calidad total, ^{González (1999}) determined that the relationships between technologies and the total quality management process as key factors for company failure or success. He concluded that the strategic application of information systems and technology focuses especially on improving the knowledge the company has regarding customer needs, reducing delivery times, and improving the quality of products/services.

Likewise, ^{Cuevas, Aguilera y González (2015}), in La relación de la innovación de procesos y el rendimiento empresarial de las MiPymes industriales de Guanajuato, considered two significant contributions. The first provided knowledge support by observing the existing relationship between the implementations that add value to processes, and business productivity in relation to MSMEs. The second contribution was the use of a new methodology to demonstrate the theoretical model by proving the constructs through second order confirmatory factor analysis and validating its hypothesis through structural equation modeling (SEM). For this, a survey was designed comprising the variables “process innovation” and “business performance” with a total of 17 items measured on a 5-point Likert scale. A Cronbach's alpha of over 0.7 was obtained from the reliability assessment of the instrument. The results obtained through structural equation modeling with the software EQS 6.1 proved the hypothesis that indicated that newness in processes influence business productivity by 66%.

In his work Análisis causal con ecuaciones estructurales de la satisfacción ciudadana con los servicios municipales, ^{García (2011}) studied the level of satisfaction perceived by users of certain types of services provided by the provincial municipality of A Coruña. The data were obtained through a survey to users of this municipality, which has 5705 inhabitants, so the study sample was 247. Five dimensions were identified through factor analysis: overall satisfaction, management, cleanliness, sanitation services and infrastructure. The structural equation modeling study was employed with the use of AMOS from 18 observed variables that constituted the survey items to study and calculate user satisfaction with municipal services; thus, causal relationships were found and those that exert a greater impact on citizens regarding decision-making were identified.

In the same way, ^{Rodríguez (2016}), in his presentation Modelo de gestión y su relación con el marco estratégico, el gobierno corporativo y la gestión del cambio, maintains that a management model in an organization should be based on processes, people and technology. Processes must be worked on and reinforced taking into account the principles of a quality management system, the continuous improvement, and the idea that technology integrates information into business processes, thus helping people to make decisions to achieve objectives.

The general objective of this article is “to design a management model including process quality and technology that strengthens the improvement of the identity registration service”. The specific objectives are “to evaluate how, following international guidelines, the management of identity registration processes will improve the identity registration service in terms of time, quality, and costs”, “to study how the digitization of documentation will improve the identity registration service in terms of time, quality, and costs”, “analyze how the systematization of biometric verification will improve the identity registration service in terms of time, quality, and costs” and “evaluate how the implementation of e-government services will improve the identity registration service in terms of time, quality, and costs”.

General Hypothesis

The design of a management model including process quality and technology improves the identity registration service.

Specific Hypotheses

Justification

Constant changes and the different organizational culture in the entities of each nation influence management systems, which also cause them to update and innovate. In this sense, this study seeks to objectively expose the development of processes based on the adoption of international standards and/or quality models, as well as new technologies adopted for service improvement.

Limitations

A limiting factor was evident when collecting the responses from citizens in relation to the questions related to the variable “technology”, since, due to the nature of this type of questions, it was possible that they were not understood, which was evidenced when analyzing the results of one of the specific hypotheses.

Another limiting factor was the access to documents and certain records due to the security of the existing information in the organization, so the researcher, in her analysis prior to the use of structural equations, took referential data for the study of the relationship of the three variables.

In relation to the authors consulted for the variables studied, about the service improvement associated with the quality of processes and technology, and applied to structural equations, the following is exposed:

Process Quality

The process management following international guidelines represents the implementation of the international standard ISO 9001:2015 to improve service, as mentioned by ^{Cruz (2001}). His most relevant conclusions are that the implementation of a quality system is motivated by competitiveness, the desire to improve service, product, and employee satisfaction, as well as to reduce costs, among others.

Likewise, ^{Pérez (2004}), in his book Gestión por procesos, points out that financial measurements that until recently were considered the most relevant do not necessarily provide data to support improvement, so other perspectives that contribute information for dynamic management are indispensable.

Technology

^{Rodríguez (2009}), in his article El AFIS del Reniec: avanzada tecnología biométrica de identificación al servicio de los peruanos y sus instituciones, points out that the Senior Management of Reniec (Peruvian National Registry of Identification and Civil Status), with a futuristic vision, took an important and historic step by deciding to acquire the Automated Fingerprint Identification System (AFIS).

In El proceso innovador y tecnológico: estrategias y apoyo público, ^{Sánchez (2008}) points out that the rapid technological changes that have occurred in recent years have made technology a key factor for competitiveness within organizations.

Service Improvement

In the first chapter of his book Mejoramiento de la calidad, un enfoque a los servicios, ^{Acuña (2005}) indicates that, in recent years, organizations are immersed in a great competition that increasingly forces them to fight for customer preferences.

Likewise, ^{Prieto (2005}), in his book El servicio en acción. La única forma de ganar todos, indicates that the population nowadays evaluates the attention it receives from companies and looks for the benefits it can find through the product; therefore, the meaning of “service” becomes relevant.

Structural Equations

^{Closas (2011}), in his article Ecuaciones estructurales, presents a statistical technique to formulate and contrast models of cause-effect relationships, and points out that it is convenient that certain areas of knowledge - when it is necessary to provide clarification of the relationship between variables, dependent (one) and independent variables (more than one), as well as the relationship that may exist between two or more hidden (latent) variables- are studied through structural equations. These multivariate statistical models involve correlation and regression to incorporate webs of interconnected variables into the study.

^{Hoyos and Ramos (2018}), indicate in their thesis that when public management does not follow proper planning, it becomes necessary to study and establish an optimal structural equation model to evaluate the overall satisfaction of the population about public services.

^{Nigro (2014}) also shows in his work that the relationships between variables are obtained from SEMs, which make it possible to assess the result and the relationships between many variables. Generally, the variables are quantitative, and a measurement instrument is used, to which a Likert scale is applied.

Sample Size

The formula was applied for a finite population, where the total population is known, and it is desired to know how many of the total should be studied:

Where: n is the sample size to be found, N is the total number of users/citizens (population), Z is the safety margin obtained from the normal distribution, p is the expected proportion of the parameter to be evaluated. For the study, N = 12 000, Z = 1.96 for a safety margin of 95%, p = .5, q = (1 - p) and the sampling error is 3%, that is to say, e = 0.03. By replacing these data in the formula, a size of 572 surveys was obtained.

The sample was selected by stratified sampling, dividing the population into strata, and selecting a sample for each stratum. Stratified sampling exposes a minimum of errors, which increases the precision of the sample (^{Hernández, Fernández & Baptista, 1998}, p.181).

Table 1 shows the details of the sample for each regional headquarters. The following is specified in each column:

JR = (From JR1 to JR16); regional headquarters name = name of each of the 16 regional headquarters; type of premises = OR (registry) or AG (agency); premises code = code assigned according to JR; premises name = name of premises according to JR, transaction per day = average number of daily procedures; sample size = stratified calculation according to formula (ni).

As the number of citizens is distributed according to the access to the different Agencies (per regions), the following formula was applied (ni):

Where ni is the sample size per premises that is to be found; n is the general sample size; N is the total number of transactions; and g is the population group (number of transactions per premises/region).

Questionnaire

The measurement instrument consisted of 21 questions related to three dimensions: “process quality”, “technology” and “service improvement”. Questions 1 to 7 belong to the dimension “process quality”; questions 8 to 14 belong to the dimension “technology”; and questions 15 to 21 belong to the dimension “service improvement” (see Appendix 1).

First, the reliability and internal consistency analysis was performed to the Likert scale applied to the questionnaire using SPSS for the survey data in its 21 items and 572 responses. An excellent result was achieved: a total Cronbach’s alpha of 0.922; that is, a reliable result that endorses a continuation of the study.

Exploratory Factor Analysis

The exploratory factor analysis (EFA) was performed by verifying that the determinant in the correlation matrix is close to zero, that is, that the variables used are linearly related, which means that the factor analysis is a pertinent technique for its analysis. Likewise, the results of the KMO = 0.851, with a significance level of 0, which demonstrate the correlation of variables.

The Varimax rotated component matrix was applied under the belief that it is possible to work with three dimensions or factors, according to theoretical considerations.

The items (questions) are then distributed in three components (factors), F1: V20, V18, V17, V19, V21, V14, V13; F2: V2, V5, V1, V4, V7, V3, V6; F3: V8, V9, V10, V12, V11. It is observed that there is an overlap of V16 and V15 in F2. They are removed, and the process is performed again, but with 19 variables. It is obtained that in the new rotated component matrix the items are also distributed in three components (factors), F1 = SERVICE IMPROVEMENT: V13, V14, V17, V18, V19, V20, V21; F2 = TECHNOLOGY: V8, V9, V10, V11, V12; F3 = PROCESS QUALITY: V1, V2, V3, V4, V5, V6, V7.

Now, for the 19 items, a total Cronbach’s alpha equal to 0.915 is obtained, which is a very positive value. Likewise, for each of the components, a Cronbach’s alpha of 0.897 was obtained for the seven elements of the component “service improvement”; 0.939 for the five elements of the “technology” component; and 0.869 for the seven elements of the “process quality” component. Additional results were obtained: KMO = 0.852, a significance level of 0 and a total variance explained that, based on Kaiser’s rule, provides a factorial structure with three factors or components that explain 65.622% of the total variance, which is appropriate, since the authors suggest a percentage of 50% or more.

Confirmatory Factor Analysis

Based on the result obtained from the exploratory factor analysis (EFA), there are 19 variables and 3 dimensions (latent variables) for the study. It is customary in EFA to use causal relationship diagrams to represent the relationships between variables and factors. In this sense, AMOS was applied to obtain the following goodness-of-fit indicators after the necessary adjustments: chi-square = 611.416, GFI = 0.900, RMSEA = 0.076, NFI = 0.929, TLI = 0.932 and CFI = 0.944. These values are within the required parameters and correspond to the confirmatory factor analysis model. Figure 1 and Table 2 show the correlations between the variables, as well as some correlations between the errors, taking into account that in order to relate two errors they must belong to the same factor. In this sense, the correlations -for example, for the factor TECHNOLOGY, between the errors of items 10 (Do you consider that the use of biometric verification (when the fingerprint is taken and compared to an existing one in the fingerprint database) is necessary to minimize identity theft? ) and 11 (Do you think that biometric verification is a tool that allows establishing high reliability security levels for the provision of services that the entities provide to their clients?)- were gradually understood. The same happened, for the factor CALIDAD_PROC, to the correlation between the errors in items 2 (Do you consider that the organization is a leader in customer-citizen service?) and 7 (Is there communication between the organization and its customers-citizens through the platform, networks, chat or other means?).

Table 2 Correlations. 

Source: Prepared by the authors.

Source: Prepared by the authors.

Figure 1 Confirmatory Factor Analysis Model (obtained with AMOS). 

Structural Equation Modeling

Structural equation modeling (SEM) is a multivariate statistical technique that assesses the outcome and relationships between several variables. These models make it possible to formulate the type and direction of the relationships expected to be found among the multiple variables, to then estimate the measures described by the theoretically proposed relationships.

Thus, the result of the CFA served as the basis for obtaining the Structural Equation Model (SEM) by using AMOS and after several processes, the best model was obtained according to the goodness-of-fit indicators: Chi-square = 364.423, GFI = 0.925, RMSEA = 0.071, NFI = 0.944, TLI = 0.945, CFI = 0.957; these results are optimal. Figure 2 and Table 3 show the correlations between the variables, as well as some correlations between the errors belonging to the same factor. For example, the factor MEJORA_SERV has the errors of items 18 (Con relación a la calidad del servicio. ¿Considera que la Organización está mejorando en la atención que le brinda? [Regarding the quality of service, do you consider that the organization is improving the service it provides?]) and 19 (Con relación al producto DNI. ¿Considera que la Organización está esforzándose por entregar un producto de calidad y sin errores? [Regarding the DNI, do you consider that the organization is making an effort to deliver a quality product without errors?]).

Table 3 SEM Correlations. 

Source: Prepared by the authors.

Source: Prepared by the authors.

Figure 2 Structural Equation Modeling (obtained from AMOS).