Paper Example Undergraduate 5,019 words

Designing a New Regulatory Framework for Telecommunications Interception and Access in Jordan

Last reviewed: April 22, 2011 ~26 min read

New Regulatory Framework for Telecommunications in Jordan

Jordan Telecommunications

QUANTITATIVE RESULTS AND ANALYSIS

Chapter X presented the pre-test results of the pilot study that used qualitative data collected from the interviews with Jordanian dignitaries. This chapter presents the quantitative results from the survey administered to the larger representative sample of respondents from Jordanian businesses.

The interviews conducted for the pilot study and a review of the literature supported the development of questions used in the survey. The interview process was used to ensure that the questions used in the research would have content validity and, thus, would accurately reflect the primary issues concerning telecommunications law. Further, the pilot study served to verify that terminology used in the survey questions showed consistent usage in the respondent sample.

Sample and Response Rate (Questionnaire)

The random stratified sample is representative of the population at large for persons affiliated with or interested in telecommunications regulation. The sample was developed to assist in making comparisons between the different categories of respondents, and to enable discrete analysis of the categorical point-of-view of the respondents concerning the telecommunications interception and access law application in Jordan.

The number of subjects contacted to participate in the questionnaire was 500. From this group, 368 completed the questionnaire bringing the response rate to 73.6, as shown in Table 8.1. This is a relatively high response rate for a survey of this type.

Table 8.1

Sample Size

Number

Percentage

Contacted Stakeholders

Respondents (Questionnaire)

73.6

The sample demographics are shown by respondent title in Table. 8.2. Respondents in the Jordanian Bar Association and Judiciary (JBA) numbered 250 out of a possible 300. This group made up 68% of the total sample. The next largest group by respondent title was 60 government officials from various agencies that consisted of 16.3% of the sample. The remaining sample groups by respondent title were Telecommunications Regulatory Commission at 7.3%, parties interested in human rights at 5.4%, and Jordanian business leaders at 3%.

Table 8.2

Sample Demographics by Respondent Title

Respondent Title

Number

# of Respondents

Percentage (%) of Sample

Jordanian Bar Association and Judiciary (JBA)

Telecommunication Regulatory Commission (TRC)

7.3

Parties interested in human rights in Jordan (HR)

5.4

Government officials from agencies such as the General Intelligence Department, Public Security Directorate (GID), and the Independent Anti-corruption Commission

16.3

Jordanian business leaders (JBL)

Total

*68=250/300 7.3=27/50 5.4=20/30-16.3=60/100 3=11/20

The sample demographics for non-responders are shown by respondent title in Table. 8.3. The percentage of non-responders overall was 26.6%, a satisfactorily low number. None of the respondent title groups show an inordinate number or percentage of non-responders. The highest percentage of non-respondents occurred in the respondent title group with the largest total number of respondents. Representation of respondents in all the other respondent title groups remains strong, with the percentage of non-respondents less than 10% within each group.

Table 8.3

Non-Responders by Respondent Title

Respondent Title

# of Non-Respondents

# of Respondents

% of Non-Respondents

Jordanian Bar Association and Judiciary (JBA)

Telecommunication Regulatory Commission (TRC)

4.6

Parties interested in human rights in Jordan (HR)

Government officials from agencies such as the General Intelligence Department, Public Security Directorate (GID), and the Independent Anti-corruption Commission

Jordanian Business Leaders (JBL)

1.8

Total

26.6

8.3 Data Analysis

The questionnaire was developed to gain information about designing a new regulatory framework for telecommunications interception and access in Jordan. The questionnaire consisted of three parts. The first section of the questionnaire consisted of data collected about the experience of the subjects related to telecommunications interception and access. The second section was used to gather data on the subjects' opinions about obstacles that apply to telecommunications interception and access law in Jordan. The third section was used to gather data about the possibility of designing a new regulatory framework for telecommunications interception and access in Jordan as affected by the research variables.

Factor analysis was used in this study to reduce the number of variables in such a way that a structural analysis would be supported. Factor analysis extracts the proportion of variance that is shared by several items and which is due to commonality (common factors). By using factor analysis, the researcher was able to use the latent variables, which are not observable, to explain the correlations between the observations. Further, the use of factor analysis permitted the error variance -- the variance not accounted for by the correlation coefficients -- to be ignored while accounting only for the variance in the correlation coefficients. A factor rotation strategy was used to obtain a clear pattern of factor loadings.

The process of diagonalizing a matrix in factor analysis allows variance to be consolidated. Eigenvalues provide information about the consolidation of variance, such that, the larger the eigenvalue, the more the variance, and the "factors with small or negative eigenvalues that are usually omitted from solutions"[footnoteRef:1] (Tabachnick and Fidell, 1996, p. 646). [1: Tabachnick, B.G., & Fidell, L.S. (1996). Using multivariate statistics (3rd Ed.). New York: Harper Collins.]

A t-test was used to determine the statistical significance between the sample distribution's mean and parameters. Structural equation modeling (SEM) used a covariance data matrix in a confirmatory manner to estimate the structural and measurement relationships implied by the hypothesized model. The SEM provides details about the key respondent groups and with regard to their perceptions and impact on decision-making related to establishing a telecommunications regulatory framework in Jordan. A Pearson correlation coefficient analysis was used to determine the discriminate validity of the survey.

A reliability analysis was conducted using statistical analysis processes such as Cronbach's alpha and hypothesis testing. These procedures are employed to gauge the reliability of the instrument to gather sufficiently robust data, which will then enable generalizations to be made regarding the probability of these findings beyond the sample to the entire population.

8.2.1 Questionnaire Validity

A pilot study was conducted by using individual open interviews to pre-test the validity of the questions to be used in the questionnaires and the interviews of the study. Face validity was addressed in the pre-test by using judgment to determine whether the questions contained items that were adequate to measure the research variables of interest. Against the background of the literature review, and through consideration of the regulatory framework for telecommunications in Australia, interview questions were developed that reflect the known relevant issues of telecommunications law and access.

Concurrent validity was tested through the interviews in the first stage of data collection. In an iterative fashion, the interview questions were tested with a representative group of subjects consisting of Jordanian dignitaries in order to ensure that the survey content accurately reflected the relevant issues of interest in the area of telecommunications law, and that any jargon used in the questions would be consistent with terminology used in the field of telecommunications regulation. An analysis of the responses gathered through the interview process and a review of the secondary data obtained through the collection of literature representing the design and implementation of interception and access law by government in Jordan and internationally, provided a test of content validity.

8.3.2 Reliability Analysis

The questionnaire in this study asked questions about the experiences and perceptions of respondents regarding the regulation of telecommunications systems in general, and about regulation related to access and interception of telecommunications as it would occur in Jordan. The pilot study functioned to address reliability issues related to the instrument itself, such as poor questionnaire construction or structural bias.

The purpose of the factor analysis is to examine the associations among variables, based on the correlations between them to see if there are underlying relationships, thereby providing a means for testing the construct validity of the questionnaire. In this research, eight factors in the questionnaire were subjected to factor analysis. The factors are national security, criminal investigation, combat terrorist, evidence, economic growth, implementing internationally, cost, and privacy. Each factor was combined with several question items that respondents would have opportunity to answer as they completed the questionnaire. These items and the factors were examined through factor analysis, the results of which are shown in Table 8.4 and Table 8.5.

Table 8.4

Factor Loadings -- Eight Variables for implementing telecommunication interception and access law in Jordan

Variables

Items

National Security

0.89

0.08

0.18

0.27

0.31

0.07

0.17

0.04

0.87

0.08

0.16

0.24

0.17

0.10

0.41

0.19

0.91

0.05

0.42

0.33

0.25

0.12

0.36

0.11

0.88

0.01

0.12

0.25

0.04

0.12

0.18

0.33

Criminal Investigation

0.28

0.73

0.19

0.12

0.08

0.29

0.17

0.22

0.23

0.72

0.33

0.28

0.19

0.11

0.12

0.23

0.24

0.87

0.34

0.15

0.17

0.18

0.12

0.15

0.25

0.82

0.35

0.24

0.15

0.17

0.22

0.33

0.12

0.86

0.22

0.16

0.18

0.22

0.25

0.31

0.22

0.86

0.21

0.08

0.17

0.23

0.28

0.16

Combat terrorist

0.02

0.17

0.86

0.41

0.12

0.19

0.29

0.17

0.01

0.22

0.89

0.25

0.16

0.22

0.18

0.12

Evidence

0.21

0.29

0.12

0.75

0.22

0.02

0.08

0.14

0.31

0.33

0.35

0.71

0.14

0.06

0.16

0.22

Economic Growth

0.12

0.08

0.32

0.09

0.70

0.08

0.04

0.15

0.12

0.21

0.11

0.76

0.12

0.05

0.09

0.22

0.14

0.06

0.76

0.14

0.11

0.32

0.22

0.19

0.15

0.78

0.22

0.16

0.06

0.15

0.23

0.22

0.04

0.89

0.23

0.18

0.05

Implementing Internationally

( Urgent Timing)

0.01

0.07

0.19

0.34

0.16

0.86

0.33

0.05

0.08

0.33

0.42

0.19

0.77

0.27

0.04

0.18

0.03

0.27

0.26

0.22

0.85

0.12

0.08

*V1 National security, V2 criminal investigation, V3 Combat terrorist, V4 Evidence, V5 Economic Growth, V6 Implementing Internationally (Urgent Timing)

The results from Table 8.4 and Table 8.5 indicate that all factor loadings were larger than 0.70%, which represented acceptable factors and items. This indicates that the factor structure was sufficiently well designed and explained.

Table 8.5

Factor Loadings -- Two Variables for Obstacle telecommunication interception and access law in Jordan

Cost

0.05

0.16

0.18

0.19

0.15

0.22

0.78

0.17

0.14

0.18

0.26

0.22

0.12

0.41

0.79

0.41

0.28

0.06

0.42

0.31

0.09

0.23

0.87

0.36

Privacy

0.04

0.09

0.34

0.27

0.19

0.23

0.15

0.89

0.19

0.33

0.38

0.22

0.11

0.15

0.06

0.88

0.21

0.37

0.22

0.18

0.06

0.14

0.09

0.75

0.06

0.12

0.24

0.26

0.22

0.09

0.22

0.71

0.15

0.18

0.26

0.28

0.25

0.11

0.17

0.87

*V 7 Cost, V 8 Privacy

Cronbach's coefficient alpha was employed to measure the reliability based on the internal consistency of the mean or average correlation for each item in the scale with other items. Factor analysis was applied directly to the correlation matrix of the original variables of the data set in order to generate first-order factors. A factor analysis was applied to the matrix of correlations among the first-order factors in order to generate second-order factors. Table 8.6 shows the number of items, from the total of 32 items in the questionnaire, that cluster under each of the first-order and second-order factors. Each Cronbach's coefficient alpha for the items and the factors is shown in Table 8.6. According to Leech et al. (2008, 2005), Cronbach's coefficient alpha should be above .70%. As shown in Table 8.6, all of Cronbach's alpha values in this research were satisfactorily above the requisite level thereby indicating satisfactory levels of internal consistency of the questionnaire.

Table 8.6

Reliability Statistics

Factors

(First and Second -- Order Factors)

# of Items

Cronbach's Alpha (?)

National Security

Implementing

0.960

Criminal Investigation

0.921

Combat Terrorist

0.929

Evidence

0.864

Economic growth

0.891

Urgent Timing

0.923

Cost

Obstacle

0.841

Privacy

0.844

Factor analysis was conducted in this research to examine the underlying structure for the 32 items related to implementing telecommunications access and intercept, and related to obstacles of implementing telecommunication interception and access. The variables are national security, investigation of crime, counter terrorist, legal evidence, economic growth, privacy, and cost. In this analysis, factor1 is implementing telecommunications interception and access law internationally, and factor 2 is telecommunication interception and access law in Jordan. The items measure the variables thought to contribute to adoption or rejection of a telecommunications regulatory framework, including those items that provide a comparison of an international telecommunications regulatory framework.

Eight variables were identified to focus on the attitudes of government officials to the implementation of the telecommunications interception and access law and insight into their orientation toward the design of such laws. These variables are shown in Table 8.7. Two variables were identified to focus on the perceptions of citizens in Jordan regarding human rights and privacy issues related to implementation of telecommunications interception and access law. These variables are shown in Table 8.8.

Table 8.7 presents the rotated factor loadings for the Jordanian and international considerations of telecommunications regulatory frameworks, and Eigenvalue, and percentage of variance. The eigenvalue for the factors in Table 8.7 is 1.055, sufficiently above the requisite 1.0 to warrant analysis. Factor 1, which is the perceptions and attitudes of respondents related to implementing telecommunication interception and access, accounts for 6.525% of the total variance. Table 8.7 illustrates the result of the rotated factor loadings which define a number of distinct clusters of interrelated data.

Table 8.7

Factor Loadings for implementing Telecommunication Interception and access

Factor

Item

Factor Loadings

Eigenvalue

% of Variance

1.055

6.525

National Security

0.89

0.87

0.91

0.88

Criminal Investigation

0.73

0.72

0.87

0.82

0.86

Combat Terrorist

0.86

0.89

Evidence

0.75

0.71

Economic Growth

0.70

0.76

0.78

0.89

Urgent Timing

0.86

0.77

0.85

*1 is National security, 2 is criminal investigation, 3 is Combat terrorist, 4 is evidence, 5 is economic growth, 6 is Implementing internationally (Urgent timing)

The results indicate that all factor loadings were larger than 0.70%, which represents acceptable factors and items. Moreover, the design for factors and items was consistent with the findings from stage one of this research.

Table 8.8 presents the rotated factor loadings for the Jordanian and international considerations of telecommunications regulatory frameworks, and Eigenvalue, and percentage of variance. The eigenvalue for the factors in Table 8.8 is 2.338, well above the requisite 1.0 to warrant analysis. Factor 2, which is the perceptions and attitudes of respondents related to the obstacles of implementing telecommunication interception and access, accounts for 15.232% of the total variance. Table 8.8 illustrates the result of the rotated factor loadings which define a number of distinct clusters of interrelated data.

Table 8.8

Factor Loadings the obstacles of implementing Telecommunication interception and access

Factor

Item

Factor Loadings

Eigenvalue

% of Variance

2.338

15.232

Cost

0.78

0.79

0.87

Privacy

0.89

0.88

0.75

0.71

0.87

*1 is Cost, 2 is Privacy

All factors and items had satisfactory alpha values that were higher than the advised 0.70% established for exploratory research. Based on the findings of these tests, it was concluded that the items and factors in the research met the various criteria for evaluation and further analysis, and demonstrated consistency with the conventions for applied factor analysis research.

Of the two factors, factor 2 is shown to be the most highly loaded and be characterized by stronger relationships to the variables. From the seminal research on factor analysis, this statement about factor loading is relevant. "It would seem that in general the variables highly loaded in a factor are likely to be the causes of those which are less loaded, or at least that the most highly loaded measures -- the factor itself -- is causal to the variables that loaded on it"[footnoteRef:2] (Cattell, 1952, p. 362). [2: Cattell, Raymond B. Factor Analysis. New York: Harper Brothers, 1952.]

Respondent reliability was estimated by using the questionnaire items and the factor scores. Three hundred and sixty-eight respondents from five different categories of telecommunications stakeholders participated in the survey research. A total of 250 members of the Jordanian Bar Association and the Judiciary were labeled JBA. Twenty-seven respondents from the Telecommunications Regulatory Commission were labeled TRC. A total of 20 individual parties interested in human rights in Jordan were labeled HR. A total of 60 officials were placed in the category labeled GID which drew from the General Intelligence Department, the Public Security Directorate, and the Independent Anti-corruption Commission. The category labeled JBL and representing Jordanian business leaders numbered 11. In all, 368 respondents completed the survey and were placed in one of the five categories.

8.4 Pearson Correlation Coefficient

In this research, reliability was analyzed through use of the Pearson Correlation Coefficient. The Pearson's Correlation Coefficients were calculated across all questionnaire items for variables 1 through 6 (national security, criminal investigation, combat terrorists, evidence, economic growth, and implementing internationally) for the following pairs of respondents by title: (JBA & GID), (JBA & HR), (HR & GID), and (TRC & JBL).

The correlations between (JBA & GID), (JBA & HR), (HR & GID), and (TRC & JBL) for each of the scored factors and items related to implementing variables are presented in Table 8.9.

Table 8.9

Pearson Correlation Coefficient between Items Across Sample Groups

(Implementing Variables)

Variable

Items

JBA & GID

JBA & HR

HR & GID

TRC & JBL

Correlation

V 1

0.745

0.895

0.982

0.920

0.765

0.862

0.782

0.799

0.892

0.798

0.985

0.866

0.843

0.874

0.882

0.872

V 2

0.879

0.878

0.865

0.984

0.789

0.879

0.972

0.985

0.897

0.856

0.892

0.856

0.999

0.897

0.980

0.990

0.975

0.942

0.830

0.880

0.984

0.978

0.834

0.998

V 3

0.876

0.891

0.856

0.783

0.937

0.955

0.977

V 4

0.896

0.978

0.834

0.947

0.788

0.952

0.856

0.658

V 5

0.856

0.876

0.988

0.975

0.822

0.778

0.849

0.998

0.733

0.888

0.910

0.897

0.911

n/a

0.850

n/a

0.875

0.856

0.992

0.987

V 6

0.955

0.830

0.970

0.834

0.990

0.834

0.957

0.760

0.885

0.760

0.998

0.891

*V1 National security, V2 criminal investigation, V3 Combat terrorist, V4 Evidence, V5 Economic Growth, V6 Implementing Internationally (Urgent Timing)

The correlations between for (JBA & GID), (JBA & HR), (HR & GID), and (TRC & JBL) each of the scored factors and items related to obstacle variables is presented in Table 8.10.

Table 8.10

Pearson Correlation Coefficient between Items Across Sample Groups

(Obstacle Variables)

Variable

Items

JBA & GID

JBA & HR

HR & GID

TRC & JBL

Correlation

V 7

0.985

0.952

0.760

0.982

0.876

0.772

0.872

0.782

0.874

0.935

0.744

0.985

V 8

0.839

0.772

0.822

0.955

0.999

0.935

0.733

0.998

0.975

0.658

0.911

0.658

0.984

0.955

0.875

0.955

0.985

0.715

0.842

0.715

*V 7 Cost, V 8 Privacy

The correlations between for (JBA & GID), (JBA & HR), (HR & GID), and (TRC & JBL) each of the scored factors and items for variables across sample groups is presented in Table 8.11.

Table 8.11

Pearson Correlation Coefficient between

Variables Across Sample Groups

Variables

JBA & GID

JBA & HR

HR & GID

TRC & JBL

Correlation

V 1

0.998

0.975

0.978

0.780

V 2

0.893

0.826

0.956

0.978

V 3

0.890

0.986

0.896

0.998

V 4

0.758

0.777

0.927

0.975

V 5

0.875

0.957

0.847

0.985

V 6

0.890

0.939

0.786

0.789

V 7

0.775

0.966

0.894

0.873

V 8

0.794

0.749

0.993

0.984

*V1 National security, V2 criminal investigation, V 3 Combat terrorist, V 4 Evidence, V 5 Economic Growth, V 6 Implementing Internationally (Urgent Timing), V 7 Cost, V 8 Privacy

All correlations between (JBA & GID), (JBA & HR), (HR & GID), and (TRC & JBL) were significant for the respondents' scores for the questionnaire items and factor scores. The correlations between factor scores show values greater than 0.70%, indicating that there is adequate reliability.

8.5 Data Screening of the Full Sample

Frequency distributions showing descriptive statistics were run on variables 1 through 8. The variables were analyzed for input accuracy, values that were out-of-range, reasonable means, reasonable standard deviations, and gaps or missing values. In addition, the variables were examined for univariate outliers and normality. All the variables show appropriate values and distributions, with the exception of the fifth item in variable 8, with an outlier value of 6.92 for skewness. There does not appear to be any missing data.

Negatively skewed distributions were detected for several of the variables. Three single item distributions were skewed at -0.20 for variable 1 which is national security, skewed at -0.20 for variable 2 which is criminal investigation, and skewed at -0.04 for variable 5 which is economic growth. For the sample size in this research, a confidence interval can be generated; the standard error of skewness would be between 0.141 and 0.122, while the margin of error would fall between 0.276 and 0.239.

Kurtosis values show a moderately wide range across the variables with a number of apparently peaked distributions and nearly equal number of flat distributions. Variable 1 which is national security has kurtosis values at 1.25 for item 3 and 1.32 for item 4, variable 4 which evidence has kurtosis values at 1.55 for item 2, variable 5 has kurtosis values at 2.15 for item 3, and variable 8 has kurtosis at 1.93 for item 1, 1.16 for item 3 and -1.36 for item 4. Of these items, five show positive skewed distributions as well. These items are as follows: In variable 1, item 3 shows skewness at 1.20; in variable 4, item 2 shows skewness at 1.54; in variable 5, item 3 shows skewness at 1.75, and in variable 8, item 1 shows skewness at 1.70, and item 3 shows skewness at 1.47.

Further examination of the distributions can include box-plots, and tests for violations of homogeneity of variance. Any desired remedies may be applied, including data transformation through the use of log, deletion of outliers, or choosing a test that is more robust to with regard to violations of assumptions about normal distributions.

Table 8.12

Descriptive Statistics for Items from 368

National security, V2 criminal investigation, V 3 Combat terrorist, V 4 Evidence, V 5 Economic Growth, V 6 Implementing Internationally (Urgent Timing), V 7 Cost, V 8 Privacy

8.6 Structural Equation Model (SEM)

To estimate the structural and measurement relationships implied by the hypothesized models, a structural equation model (SEM) was employed. The SEM allows testing whether the variables are interrelated through a set of linear relationships by examining the variances and co-variances of the variables. In this research, the SEM presents cross-sectional variation across the research respondents to yield findings about relationships.

Hypotheses were generated to provide a framework and overview of the Jordanian government's needs and the challenges that must be faced to design a new regulatory system of interception and access of telecommunications law. The path diagram in Figure 8.1 illustrates the postulated relationships between the research variables and these hypotheses.

Figure 8.1

Structural Equation Model (SEM)

(First and Second-Order Factors) with hypotheses

Implementing Telecommunications

Interception and Access Law in Jordan

(F2)

Privacy

(V7)

H 6

National

Security

Counter Terrorist

(V3)

Legal Evidence

(V4)

Economic Growth

(V5)

Cost (V6)

nvestigation crime

(V2)

Implementation Telecommunication Interception and access Internationally (F 1)

Statistical tests, parameter estimates, and standard errors were generated to examine the numerical coefficients in the linear equations. The covariance data matrix for the SEM is shown in Figure 8.13. On the path diagram, latent variables are shown in the ovals and manifest variables are shown in the boxes.

The structural equation model as represented by the path diagram is considered to be a good fit to the data. As such, the model is a useful approximation of to the respondents' perceptions, experiences, and opinions about the regulatory framework for telecommunications interception and access regulatory framework in Jordan, and it provides a reasonable explanation of the data trends.

Table 8.13

Fit Indices and Statistics for Structural Equation Model (SEM)

Statistic

Structural Model

Chi -- Square

Mardia's Normalised Estimate

9.20

Free Parameters

Fixed Parameters

CFI-ML

0.920

CFI-Robust

0.920

SRMR

0.069

RMSEA-ML

0.087

RMSEA-Robust

0.084

The Chi-Square goodness of fit measure permits the comparison of the categorical data with a theoretical expected distribution, as in the structural equation model. At 180.50, the value of Chi-Square is below the critical value (3.841) for 0.05 probability level. It is important to note that Chi-Square is largely a function of sample size. The Root Mean Square Error of Approximation (RMSEA) is well above the desired 0.05 level, but sufficiently below the 1.0 level to warrant consideration. The Standard Root Mean Residual (SRMR) is above, but approaching, the desired 0.05 level. The Comparative Fit Index (CFI) values are largely dependent on the average size of the correlations between variables in the data. At 0.920, these values are indicative of strong correlations.

8.7 Questionnaire Discussion

Questionnaire respondents exhibit a high degree of agreement regarding the variables associated with factor 1, the barriers associated with implementing a regulatory framework for telecommunications interception and access in Jordan. Issues about privacy and cost are perceived as substantial challenges to the implementation of telecommunications regulations regarding interception and access. Respondents also agree strongly that there is a relationship between economic growth and the implementation of telecommunication interception and access law in Jordan.

The greatest agreement among respondents by title pairs occurred for (JBA & HR) and (TRC & JBL). Agreement was high for the Jordanian Bar Association (JBA) respondents and the parties interested in human rights (HR) for all variables except variable 2, which is criminal investigation, variable 4, which is evidence, and variable 8, which is implementing internationally. The second title pair that resulted in high agreement across variables was for members of the Telecommunication Regulatory Commission (TRC) and the Jordanian Business Leaders (JBL). This group showed strong agreement for all variables except variable 1, which is national security, variable 6, which is implementing internationally, and variable 7, which is cost.

Three of the four title pairs agree that variable 1, which is national security is related to the implementation of a regulatory framework for telecommunications interception and access. The only two variables that did not receive strong agreement from the at least two of the title pairs were variable 6, which is implementing internationally, and variable 7, which is cost. All other variables received strong agreement from at least two title pairs.

8.7.1 Relationships between factors and variables

The path diagram in Figure 8.2 illustrates the relationships between the first- and second-order factors. Factor 1 is exogenous (not caused) and factor 2 is endogenous (caused). No disturbances are shown in the diagram. The weakest relationships occur for variable 1 (V1) which represents items related to national security and variable 6 (V6) which represents items related to implementing internationally (or urgent timing). The strongest relationships occur for variable 4 (V4) at .80, which represents items related to evidence and variable 7 (V7) at 0.82, which represents items related to cost (V7). Variable 8 (V8) which represents items related to privacy does not appear in the diagram.

Figure 8.2

Structural Equation Model (SEM)

(First and Second-Order Factors)

V 1

V 2

E1 2.821 0.55

E2 2.778 0.70

E3 2.552 0.78

0.95

E4 4.105 0.80

E5 2.785 0.75

E6 3.044 0.65

E7 8.380 0.82

The value of the other variables on the path diagram indicate moderate relationships. The value for variable 2 (V2) which represents items related to criminal investigation is 0.70. The value for variable 3 (V3) which represents items related to combat terrorism is 0.78. The value for variable 5 (V5) which represents items related to economic growth is 0.75.

8.7.2 Hypothesis Testing and Control Variables

Were you going to use a t-test for this section? I did not find the t-test data.

Seven research hypotheses were stated in this research. They are listed below.

H1a: There is possibility of applying telecommunication interception and access telecommunications law widely in Jordan.

H2a: There is relationship between national security and implementing telecommunication interception and access law in Jordan.

H3a: There is relationship between Investigation crime and implementing telecommunication interception and access law in Jordan.

H4a: There is relationship between and combat terrorist implementing telecommunication interception and access law in Jordan.

H5a: There is relationship between legal evidence and implementing telecommunication interception and access law in Jordan.

H6a: There is relationship between Economic growth and implementing telecommunication interception and access law in Jordan.

H7a: There are obstacles to applying telecommunications interception and access law in Jordan.

H8a: Implementing telecommunication interception and access law internationally positively affects on implementing telecommunication interception and access law in Jordan.

8.8 Results and Analysis of Section B

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