Some Theoretical and Practical Issues on the Quality of Mobile Information Services of

The Standard Deviation of all mobile service quality attributes is represented by: (1) the relative importance of the attributes and (2) the level of performance. Then, the average values of importance and level of performance are used to determine the individual attributes on the graph. Through this graph, the enterprise will know the priority order of quality attributes to take actions to improve them.

4.2.3.1. Data processing

a. Data cleaning

The collected questionnaires are checked to eliminate inappropriate responses before processing and analyzing the data. After entering the data into the computer, it is often not possible to process and analyze it immediately due to many reasons such as errors, omissions, and redundancies due to data entry errors and eliminating observations with unusual scores by using descriptive statistical tests from frequency tables for simple questionnaires or combined tables for complex questionnaires.

b. Descriptive statistics and inferential statistics

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Descriptive statistics allow researchers to present the data collected in a structured and summarized form (Huysamen, 1990). The descriptive statistics used in this study to analyze and describe the data include frequencies, proportions, means, and standard deviations.

Descriptive statistics are used to describe the basic characteristics of data collected from experimental studies in various ways. Descriptive statistics provide simple summaries of samples and measures. Together with simple graphical analysis, they form the basis of any quantitative analysis of data. The first step in describing and understanding the distributional characteristics of a table of raw data is to create a frequency distribution table. Then, using some functions to clarify the characteristics of the analyzed sample. To understand phenomena and make appropriate decisions, it is necessary to grasp the basic methods of data description. Some of the techniques applied are as follows:

- Graphical representation of data in which graphs describe data or help compare data.

- Represent data into tables that summarize the data.

- Summary statistics (in the form of single statistical values) describe the data.

Inferential statistics studies the randomness and error of data sets, from which it models and makes inferences about the population. These inferences can be true or false answers to hypotheses (statistical hypothesis testing), estimating population parameters (estimation), describing the interaction of variables (correlation), modeling relationships between variables (regression), and interpolating unobservable values (extrapolation, interpolation).

c. Assess the reliability and validity of the scale

Evaluate the scale using Cronbach's alpha coefficient:

Cronbach's alpha coefficient is a statistical test of the degree of consistency with which items in a scale are correlated with each other (Hoang Trong & Chu Nguyen Mong Ngoc, 2005). This coefficient assesses the reliability of the measurement based on calculating the variance of each item and calculating the correlation of each item's score with the total score of the remaining items of the measurement.

This method allows the analyst to eliminate inappropriate variables and limit junk variables during the research process and evaluate the reliability of the scale by coefficient through Cronbach's alpha coefficient. When evaluating the suitability of each item, items with item-total correlation coefficient greater than or equal to 0.3 are considered items with guaranteed reliability (Nguyen Cong Khanh, 2005), items with item-total correlation coefficient less than 0.3 will be removed from the scale.

Many researchers agree that a Cronbach's alpha coefficient of each scale from 0.8 or higher to close to 1 is a good measurement scale; from 0.7 to close to 0.8 is usable. Some researchers also suggest that a Cronbach's alpha coefficient of 0.6 or higher is usable in cases where the concept under study is new or new to the respondents in the research context (Nunnally, 1978; Peterson, 1994; Slater, 1995 cited by Hoang Trong & Chu Nguyen Mong Ngoc, 2005). Therefore, for this study, an alpha coefficient of 0.6 or higher is usable.

Assessing the validity of the scale: Exploratory factor analysis EFA

Exploratory Factor Analysis (EFA) was used to evaluate the validity of the scale (Nguyen Cong Khanh, 2005). In this study, EFA analysis used the principal component method with the

Varimax rotation and stopping point when extracting factors with eigenvalues ≥ 1 are used. During the EFA analysis, items and scales that do not meet the requirements will be eliminated. The selection criteria are that items must have factor loading > 0.4, total extracted variance ≥ 50% (Gerbing & Anderson, 1998 cited by Tran Thi Kim Loan, 2009). In addition, the coefficient of the KMO (Kaiser-Meyer-Olkin of Sampling Adeqacy) test > 0.5 and the Bartlett Test of Sphericity has a significance level < 0.05 (Hair et al., 2006 cited by Le Van Huy, 2009).

Computationally, factor analysis is somewhat similar to multiple regression analysis in that each variable is represented as a linear combination of underlying factors. The amount of variation in a variable explained by the common factors in the analysis is called communality. The common variation in variables is described by a small number of common factors plus one factor that is unique to each variable. These factors are not explicitly stated. We can choose factor weights or weights so that the first factor explains the largest part of the total variation. We then choose a second set of weights so that the second factor explains the majority of the remaining variation and is uncorrelated with the first factor. This principle is applied in the same way to the subsequent weights. Thus, factors are estimated so that their weights, unlike the values of the original variables, are uncorrelated with each other. Furthermore, the first factor explains the most variation in the data, the second factor explains the second most, etc.

Regression correlation analysis

Correlation analysis: Correlation is a necessary condition for regression analysis, so if the independent variable is not correlated with the dependent variable, we will remove this independent variable from the regression analysis. The condition for statistical significance is Sig.(2-tailed) < 0.05, which means that the two variables are correlated with each other. The correlation coefficient has a value from -1 to 1, a positive correlation coefficient represents a positive relationship, a negative correlation coefficient represents a negative relationship, the larger the correlation coefficient between factors, the closer the relationship between dependent and independent variables.

Regression analysis: The hypotheses of the research model will be tested by performing regression analysis. The regression analysis method aims to determine

the important role of each factor. After running the regression model, evaluate and test the parameters of the regression analysis step. The higher the standardized Beta coefficient of a variable, the greater the impact of that variable on the quality of customer care services. The significance level established for the tests and analysis is 5% (95% confidence level).

4.2.4. Research process

Identify the problem

study

Research objectives

rescue

Theoretical basis

Collect,

import, clean numbers

Board design

ask

Build

scale

Statistics, sample description

rescue

Cronbach reliability test

alpha

Exploratory factor analysis

break EFA

Analysis of the importance level model – level

IPA implementation

Analysis

correlation and

regression

Figure 1.1: Research process

Step 1: Identify the research problem : acceptance and use of mobile information services of VNPT Thua Thien Hue.

Step 2: Research objective : explore the fit with the theoretical framework.

Step 3: Theoretical basis : concepts and research models related to the problem

research topic

Step 4: Building the scale: design and build the scale according to the theoretical framework

Step 5: Design the questionnaire

Step 6: Collect, enter and clean data.

Step 7: Descriptive statistics of the research sample

Step 8: Cronbach alpha reliability test : eliminate variables with high correlation coefficients.

overall (<0.3), cronbach alpha coefficient test (>0.6).

Step 9: Exploratory factor analysis EFA : remove variables with EFA weight <0.5; check KMO coefficient, check extracted variance (>50%).

Step 10: Regression correlation analysis

Step 11: Analyze the IPA importance-performance model

5. Structure of the topic

The structure of the topic is as follows:

PART I: PROBLEM STATEMENT

PART II: RESEARCH CONTENT AND RESULTS

Chapter 1: Some theoretical and practical issues on the quality of mobile information services

The movement of telecommunications enterprises

Chapter 2: Application of IPA method to measure the quality of mobile information services

VNPT Thua Thien Hue's activities

Chapter 3: Some solutions to improve the quality of mobile information services of VNPT Thua Thien Hue

PART III: CONCLUSION AND RECOMMENDATIONS

PART II: RESEARCH CONTENT AND RESULTS

CHAPTER 1: SOME THEORETICAL AND PRACTICAL ISSUES ON THE QUALITY OF MOBILE INFORMATION SERVICES OF THE COUNTRIES

TELECOMMUNICATIONS ENTERPRISE

1.1. Theoretical basis

1.1.1. Service concept

Nowadays, in the context of globalization, service and service quality are no longer a new category in economics. Therefore, there are many ways to present the concept of service.

In the Oxford dictionary, service technology is defined as “providing services, not goods” or providing something “intangible”.

According to James Fitzsimmons, service is an intangible, perishable experience delivered to customers (customers act as service providers).

In Marketing theory, services are considered as activities provided by one entity to another, they are intangible and do not change ownership. Services can be performed but are not necessarily associated with physical products.

Services are actions, processes, and ways of performing a certain task to create value for customers, satisfying their needs and expectations (Zeithaml & Britner, 2000). Services are activities or benefits that businesses can contribute to customers to establish, strengthen and expand long-term relationships and cooperation with customers (Kotler & Armstrong, 2004). Gronroos (1990) defines “Service is an activity or a series of activities that are more or less intangible, usually but not necessarily, taking place in interactions between customers and service staff and/or physical resources or goods and/or service delivery systems provided as solutions to customer problems”. Kotler (2000) stated that “A service is any act or performance that one party can offer to another that is essentially intangible and does not result in the ownership of anything. Its product may or may not be tied to a physical object.

with a physical product”.

According to the definition of the International Organization for Standardization (ISO 9004-1991E): "Service is the result of the interaction between the supplier and the customer, as well as the supplier's activities to meet the needs of consumers". This is a widely used concept. The nature of service is a process of activities including intangible factors, resolving the relationships between the supplier and the customer or the customer's assets without changing ownership. Thus, service is the result of activities that are not expressed by physical products, but by their usefulness and economic value. Service is a special product, with many characteristics different from other types of goods such as intangibility, inseparability, heterogeneity and impossibility of storage. It is this characteristic that makes service difficult to quantify and cannot be identified by the naked eye.

Intangible:

Intangibility, according to Miner (1998), there is no such thing as a product or service and he argues that there is a continuum between tangible and intangible products. Parasuraman et al. (1985) also commented that intangibility means that “most services cannot be measured, counted, catalogued, tested and certified before they are provided to ensure service quality. Unlike physical products, services cannot be seen, tasted, smelled, felt or heard before they are purchased. Services are activities provided by businesses, unlike tangible goods, we cannot see, taste, touch or feel them before we consume them.

It is difficult to evaluate the benefits of using a service before buying it, so choosing to buy the service is also more difficult. To consume their services, businesses need to influence buyers in every way so that they quickly see the benefits of using the service, the convenience and quality of the service as well as the reasonableness of the service price.

Heterogeneous:

The quality of services depends on who creates them because those who create the products

Service products have different capabilities and in different environmental conditions, circumstances, and psychological states, which can lead to different quality, especially in non-standardized conditions (machines, skills, technology, etc.). Because customers really want to be cared for as individual people, services are often personalized and inconsistent. This characteristic is also called service differentiation. Accordingly, service implementation is often different depending on the service method, service provider, service person, implementation time, service area, service object and service location. Therefore, it is very difficult for businesses to set service standards to satisfy all customers in all circumstances because that satisfaction depends on the perception and expectation of each customer. This characteristic is most evident in services that involve high labor. Demanding consistent quality from employees is difficult to ensure (Caruana & Pitt,1997). The reason is that what the company intends to serve may be completely different from what the consumer receives.

Differentiation, the service performed will be different in each different type, such as the service provided in mobile information is different in the banking sector, or in the tourism sector. On the other hand, the quality of service depends on the perception of the customer. Therefore, the consumption of service products also arises more difficult problems than the consumption of other material products.

Inseparable:

The inseparability of services is reflected in the difficulty in dividing services into two distinct stages: the production stage and the use stage. This is a characteristic that shows the difference between services and goods. For physical goods, the production and consumption processes are separate. People can produce goods in a different place and at a different time from the place of sale and the place of consumption. For services, production and consumption of services take place simultaneously and the interaction between the service provider and the service recipient can affect the quality of the service. In most hotel and restaurant services, both the service provider and the customer cannot be separated. The customer's contact with the staff is an important part of the product. This characteristic shows that the interaction between the provider and the customer creates the consumption of the service produced when selling, the product

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