This study investigates the impact of HEdPERF on students’ satisfaction and academic performance in Ghanaian private universities, with students’ attitude towards learning as a mediator. The study was conducted on a total of 600 students selected from 6 private universities in Ghana out of which 421 responses received were useable representing 70.16% response rate. Purposive and convenience sampling techniques were adopted in selecting respondents. Questionnaire was used to collect data. Explanatory research design was also used. Stata version 13 and IBM Statistical Package for Social Sciences version 20 were the software used in data analysis. The study made use of Structural Equation Model (SEM) for data analysis and explored direct, indirect and total effect relationships. Confirmatory Factor Analysis (CFA) was used for data purification. The research found that HEdPERF has positive and statistical significant relationships with students’ satisfaction, attitude towards learning and academic performance. Attitude towards learning also has positive and statistical significant relationship with students’ satisfaction and academic performance. As regards the mediation effect, attitude towards learning partially mediates between HEdPERF on one hand, and students’ satisfaction and academic performance on the other. This means that managers of Private Universities should consider service quality effects on students’ satisfaction and academic performance with and without attitude towards learning in their strategic management.
The higher education sector is becoming increasingly competitive and is characterised with the presence of domestic and international educational institutions, varied forms of institutional collaborations, and students with higher levels of expectations [
This study focuses on students’ satisfaction and academic performance because these constructs play a significant role in churning out graduates who are potential great leaders and the required labour force for a country’s economic and social development [
The provision of outstanding service quality is generally recognised as a vital business requirement. Service quality is not just corporate offering and a competitive weapon, it is also an essential corporate profitability and survival tool. However, service quality within the service sector has remained a complex concept. The high growth of the educational market has called for a comprehensive service quality measurement scale for higher education. In response to this, [
[
Service quality has emerged to be an all-encompassing strategic force and important strategic tool for management researchers and industry practitioners. Many researchers have developed different service quality measurement scales for varied sectors. It is not also difficult to witness a number of opinions on how to accurately measure service quality to understand its essential antecedents and consequences for improving quality to achieve competitive advantage that can impact on satisfaction and higher academic performance. In line with the thinking of [
The predominant service quality scales used by many researchers and industry practitioners are the SERVQUAL [
Author | Scale developed | Industry |
---|---|---|
[ | SERVQUAL | General |
[ | LODGSERV | Hospitality |
[ | SERVPERF | General |
[ | LODGQUAL | Hospitality |
[ | RSQS Retail | Retail |
[ | HEdPERF* | Higher education |
[ | HEDQUAL | Higher education |
[ | CUL-HEdPERF | Higher education |
*service quality measure used in the study.
scale called HEdPERF that was based on the SERVPERF scale, which considered the specific determinants of service quality in higher education. [
Most of the research works in higher education institutions have produced confirmation that service quality leads to students’ satisfaction [
[
H1: Service quality positively and significantly affects student’s satisfaction.
Students’ academic performance measurement has received considerable attention in different research works and has become a challenging topic in academic literature. The students’ academic performance plays an important role in creating the finest quality alumni who provides material support and play ambassadorial role for academic institutions. Good academic performance can lead to lower marketing cost, enhance opportunity for brand extension and increased market shares. Academic performance can also promote favourable word of mouth and greater resistant among loyal students to competitive strategies which can lead to lower levels of price sensitivity among students and parents. Students’ academic performance is also an important antecedent to the design and implementation of academic policies which aim to improve quality in education by changing attitude of students towards learning [
Many research works measure students’ academic performance by using Cumulative Grade Point Average (CGPA), Grade Point Average (GPA) or the latest results as a convenient summary measure of their students’ academic performance. Some researchers have argued that, the GPA gives a better measurement insight into the relative level of performance of individual and different group of students. Other researchers assessed the performance of students through the previous year’s results or an outcome of a particular course [
Several studies have been conducted to find out the factors that affect academic performance of students. Some researchers have demonstrated that students’ academic performance depends on factors like psychological, economic, social, personal and environmental factors. [
A number of research works have also focused on factors that affect students’ academic performance in higher education. [
H2: Service quality positively and significantly affects academic performance.
The behavioural theory used in the review of attitude towards learning relationship with academic performance and satisfaction constructs is based on the theory of reasoned action and theory of planned behaviour. The theory of reasoned action is about the relationship between the attitude and behaviour. According to [
Several scholars have attempted to define the word “attitude” in different ways, however, there is no agreed definition so far for attitude. [
Some researchers have examined the role students’ study habits and their attitudes towards learning have on academic performance. [
H3: Attitude towards learning positively and significantly affects academic performance.
Learning is an individual action which confronts the learner with the risk of going to an unknown place in the end. For most of the teachers, a good student is the one who is eager to learn and has positive attitudes towards learning. According [
H4: Attitude towards learning has positive and significant relationship with students’ satisfaction.
Attitude could be defined as a consistent tendency to react in a particular way often positively or negatively toward a given matter or social object. Students have attitude towards learning, but not all have the same attitude towards it. Some students’ attitudes propel them along, helping them to achieve high academic performance and become satisfied. Others have attitudes that slow them down or stop them from learning [
Students with positive attitude towards learning make significantly better academic achievement than their counterparts with negative attitude towards school. Good attitude towards learning could be reinforced in line with specifications in operant conditioning theory of learning (as cited by [
H5a: Attitude towards learning has full mediation effect on the relationship between service quality, and academic performance.
H5b: Attitude towards learning has full mediation effect on the relationship between service quality, and students’ satisfaction.
This study is an applied research in terms of its objectives, it is quantitative in terms of data collection and analysis, and it is explanatory research design to establish causal relationships among service quality, satisfaction, academic performance, and attitude towards studies. The statistical community of this study consists of students in the private universities in the Ashanti Region of Ghana. Samples of 600 students were selected from six private universities with 100 from each institution. [
The HEdPERF dimensions which measured service quality was adapted from [
Measures and Items Retained | Factor Loadings | T values | Cronbach’s Alpha | Construct Validity | Highest VIF | AVE | Highest Correlation | |
---|---|---|---|---|---|---|---|---|
Non-Academic Aspect | Item 1 | 0.6908055 | 19.94 | 0.7837 | 0.792 | 1.59 | 0.652 | 0.5743 |
Item 2 | 0.7275884 | 22.05 | ||||||
Item 3 | 0.6359725 | 17.05 | ||||||
Item 4 | 0.6077025 | 15.60 | ||||||
Item 5 | 0.5806738 | 14.44 | ||||||
Academic Aspect | Item 1 | 0.5436257 | 11.56 | 0.6689 | 0.752 | 2.26 | 0.634 | 0.6013 |
Item 2 | 0.5202072 | 10.73 | ||||||
Item 3 | 0.8139375 | 17.43 | ||||||
Item 4 | 0.4620713 | 9.59 | ||||||
Reputation | Item 1 | 0.6839061 | 17.52 | 0.7235 | 0.760 | 2.07 | 0.727 | 0.6446 |
Item 2 | 0.7811469 | 20.56 | ||||||
Item 3 | 0.6034162 | 14.37 | ||||||
Access | Item 1 | 0.4918744 | 10.53 | 0.7067 | 0.831 | 1.45 | 0.729 | 0.5051 |
Item 2 | 0.653702 | 13.98 | ||||||
Item 3 | 0.8909986 | 17.19 | ||||||
Programme Issues | Item 1 | 0.7504859 | 23.82 | 0.7990 | 0.802 | 1.99 | 0.704 | 0.5903 |
Item 2 | 0.6878366 | 20.11 | ||||||
Item 3 | 0.7017046 | 20.80 | ||||||
Item 4 | 0.6867334 | 19.92 | ||||||
Students Satisfaction | Item 1 | 0.6177804 | 15.90 | 0.7750 | 0.786 | 1.00 | 0.688 | 0.5675 |
Item 2 | 0.6426371 | 16.98 | ||||||
Item 3 | 0.7188582 | 20.97 | ||||||
Item 4 | 0.7487615 | 22.48 | ||||||
Academic Performance | Item 1 | 0.6348772 | 16.68 | 0.7602 | 0.782 | 1.00 | 0.679 | 0.5675 |
Item 2 | 0.768365 | 23.05 | ||||||
Item 3 | 0.6567591 | 17.38 | ||||||
Item 4 | 0.6091828 | 15.53 | ||||||
Attitude towards Learning | Item 1 | 0.6886163 | 21.62 | 0.8276 | 0.841 | 1.26 | 0.686 | 0.5682 |
Item 2 | 0.7207222 | 23.80 | ||||||
Item 3 | 0.8254607 | 33.15 | ||||||
Item 4 | 0.6493537 | 19.01 | ||||||
Item 5 | 0.5439614 | 13.69 |
Source: Author Field work, 2016.
Items | Variables | Factor Loadings | T |
---|---|---|---|
Non-Academic Aspect | |||
1 | There is systematic and reassurance in solving problems | 0.6908055 | 19.94 |
2 | My University keeps to its promises | 0.7275884 | 22.05 |
3 | My University is dependable in all times | 0.6359725 | 17.05 |
4 | My University responds to request promptly | 0.6077025 | 15.60 |
5 | My University provides services within a reasonable time periods | 0.5806738 | 14.44 |
Academic Aspect | |||
1 | I gain a lot of knowledge in course content in my University | 0.5436257 | 11.56 |
2 | There is always feedback from academic assignments | 0.5202072 | 10.73 |
3 | There is excellent quality programmes | 0.8139375 | 17.43 |
4 | There is sufficient consulting time for academic issues | 0.4620713 | 9.59 |
Reputation of university | |||
1 | I feel secured dealing with my University | 0.6839061 | 17.52 |
2 | I have total trust with my University | 0.7811469 | 20.56 |
3 | My school operates in religious-like manner | 0.6034162 | 14.37 |
Access | |||
1 | The non-academic staff are approachable in times of need | 0.4918744 | 10.53 |
2 | It is easy to contact academic staff for information | 0.653702 | 13.98 |
3 | It is easy to contact non-academic staff for information | 0.8909986 | 17.19 |
Programme Issues | |||
1 | The syllabus is flexible | 0.7504859 | 23.82 |
2 | Prompt dealing with complaints with programme issues | 0.6878366 | 20.11 |
3 | There are excellent academic programmes | 0.7017046 | 20.80 |
4 | There are available information on programmes | 0.6867334 | 19.92 |
Students Satisfaction | |||
1 | I am satisfied with the university learning services | 0.6177804 | 15.90 |
2 | Overall, I am happy with the specialization I have chosen. | 0.6426371 | 16.98 |
3 | I am happy with the academic work of the University | 0.7188582 | 20.97 |
4 | I am satisfied with the lecturers that impact knowledge | 0.7487615 | 22.48 |
Academic Performance | |||
1 | I am consistent with quality of my academic work | 0.6348772 | 16.68 |
2 | I quickly learn new materials apart from my course of study | 0.768365 | 23.05 |
3 | My grading point merits my efforts | 0.6567591 | 17.38 |
4 | I have improved my reading skills | 0.6091828 | 15.53 |
Attitude towards Learning | |||
1 | I consider learning to be enjoyable | 0.6886163 | 21.62 |
2 | I continue with difficult problems even if I can’t do it | 0.7207222 | 23.80 |
3 | I show interest in dealing with difficult subjects | 0.8254607 | 33.15 |
4 | I have no troubles learning concepts | 0.6493537 | 19.01 |
5 | I enjoy working with others to solve problems | 0.5439614 | 13.69 |
developed from these authors but after the CFA purification, 4 variables were selected based on the fit indices. The students’ satisfaction scale was adapted from [
To evaluate the reliability and validity of the HEdPERF dimensions, students’ satisfaction, academic performance and attitude towards learning constructs, CFA was run and refined using Stata 13 to show a good fit. The final CFA results show a good fit to the data. After purification, numerous items were removed from the models because they loaded poorly on the factor. The criterion used was 0.4 as advised by [
To check whether the strength of correlation among the variables will affect further
Dimension/Construct | chi-square | degrees of freedom | p-value | RMSEA | CFI | SRMR |
---|---|---|---|---|---|---|
Non-Academic | 6.04 | 5 | 0.3027 | 0.022 | 0.998 | 0.017 |
Academic | 1.68 | 2 | 0.4306 | 0.000 | 1.000 | 0.012 |
Reputation | 8.51 | 2 | 0.0142 | 0.089 | 0.979 | 0.026 |
Access | 0.00 | 0.00 | 0.00 | 0.000 | 1.000 | 0.000 |
Programme Issues | 2 | 3.36 | 0.1867 | 0.041 | 0.997 | 0.012 |
Students Satisfaction | 2 | 3.31 | 0.1908 | 0.040 | 0.997 | 0.013 |
Academic Performance | 5 | 11.39 | 0.0441 | 0.056 | 0.985 | 0.025 |
Attitude towards Learning | 5 | 3.96 | 0.5557 | 0.000 | 1.000 | 0.012 |
Notes: χ2 = Chi-square d.f. = Degree of freedom; χ2/d.f = normed Chi-square; RMSEA = Root mean standard error of approximation; CFI = Comparative fit index; SRMR = Standardized mean square residual; TLI = Tucker Lewis Index.
statistical analysis; a multicollinearity test was run using the Pearson correlation statistics. For robustness, it is recommended that the correlation statistics should not exceed 0.7 [
The work involved a sample of 600 students out of which 412 responses were received. It was found that most of the respondents are females, (236) representing 57.3% and 176 representing 42.7% are males after a descriptive summary was done. Even though the males are more than the females in tertiary institutions, more females participated in the study. Looking at the age distribution of the respondents, it was observed that the majority of the respondents, 220 (representing 53.4%) fall within 20 - 30-year age bracket. This is followed by respondents whose ages are between 31 - 40 years (91) representing 22.1%. A total of 69 respondents representing 16.7% fell under 20 years and only one matured student who is above 50 years. The general observation is that, youngest and vibrant youths are devoting much time and effort to improve their education and hence working and attending school at the same time. On the whole, students studying business related courses such as Accounting, Marketing, Human Resource Management, and Procurement studies dominated student’s enrolment in private universities in Ghana. On the programme of study, 331 respondents are studying business related courses representing 56.1% whiles 181 respondents representing 43.9% are pursuing other tertiary courses.
NAA | AA | REP | ACC | PI | SAT | PERF | ATL | |
---|---|---|---|---|---|---|---|---|
NAA | 1 | |||||||
AA | 0.5743** | 1 | ||||||
REP | 0.5002** | 0.6013 | 1 | |||||
ACC | 0.3495 * | 0.4085** | 0.4788** | 1 | ||||
PI | 0.4705* | 0.6207* | 0.5944* | 0.5051* | 1 | |||
SAT | 0.3610** | 0.5643** | 0.6446** | 0.4254** | 0.5903 | 1 | ||
PERF | 0.3275** | 0.5256* | 0.4838* | 0.3776** | 0.5046* | 0.5675* | 1 | |
ATL | 0.3588** | 0.4974** | 0.5682 | 0.4312** | 0.4913* | 0.5342* | 0.4784* | 1 |
NAA = Non-Academic Aspect; AA = Academic Aspect; REP = Reputation of university; ACC = Access; PI = Programme Issues; SAT = Students Satisfaction; PERF = Academic Performance; ATL = Attitude towards Learning.
The study analysed the relationship between HEdPERF dimensions on one hand, and students’ satisfaction and academic performance on the other.
Variables | Frequency | Percentage (%) |
---|---|---|
Gender | ||
Male | 176 | 42.7 |
Female | 236 | 57.3 |
Age distribution | ||
under 20 years | 69 | 16.7 |
20 - 30 years | 220 | 53.4 |
31 - 40 years | 91 | 22.1 |
41 - 50 years | 31 | 7.5 |
51 years and above | 1 | 0.2 |
Programme of Study | ||
Business Administration | 231 | 56.1 |
Others course | 181 | 43.9 |
As regards HEdPERF dimensions relationship with academic performance, non-academic aspect again has negative relationship with academic performance and it is not statistically significant. The academic aspect and programme issues have positive relationship with academic performance and are statistically significant. The reputation and access dimensions have positive relationships with academic performance but they are not statistically significant. These findings also mean that academic aspect and programme issues can predict improvement in students’ academic performance.
Dimension | Coefficient | OIM Std Err | Z | P-Value | 95% Conf. |
---|---|---|---|---|---|
Students’ Satisfaction | |||||
Non-academic | −0.0773044 | 0.0465167 | −1.66 | 0.097 | −0.1684756 |
Academic | 0.1835234 | 0.0576548 | 3.18 | 0.001 | 0.070522 |
Reputation | 0.4137541 | 0.053665 | 7.71 | 0.000 | 0.3085726 |
Access | 0.063491 | 0.0394763 | 1.61 | 0.108 | −0.013881 |
Programme issues | 0.2470384 | 0.0473694 | 5.22 | 0.000 | 0.154196 |
Academic Performance | |||||
Non-academic | −0.0173047 | 0.0433276 | −0.40 | 0.690 | −0.1022251 |
Academic | 0.2128086 | 0.0541771 | 3.93 | 0.000 | 0.1066235 |
Reputation | 0.0218809 | 0.0532919 | 0.41 | 0.681 | −0.0825693 |
Access | 0.0624428 | 0.036762 | 1.70 | 0.089 | −0.0096094 |
Programme issues | 0.1056816 | 0.0454029 | 2.33 | 0.020 | 0.0166935 |
The findings of the study show a positive and statistically significant relationship among HEdPERF, students’ satisfaction, attitude towards learning and academic performance constructs. This implies that, HEdPERF as a measure of service quality at higher education favourably affects students’ satisfaction and academic performance. This has supported H1 and H2. Attitude towards learning also has positive relationship between academic performance and students’ satisfaction. These findings also support H3 and H4 respectively.
These findings from Ghana’s higher education context show that service quality positively and significantly affect students’ satisfaction. This means that when service quality improves students’ satisfaction goes up. This finding supports the work of [
In addition, students’ attitude towards learning can predict students’ satisfaction and academic performance when the variance in the model is controlled for. The finding supports the work of [
academic performance, revealed a high correlation between students’ academic performance and study habits. The finding again corresponds with the findings of [
Mediation seeks to identify and explicate the mechanism that underlies an observed relationship between an independent variable (HEdPERF) and a dependent variable (Students’ Satisfaction and Academic Performance) via the inclusion of a third explanatory variable, known as the mediator (Attitude Towards Learning). Rather than hypothesizing a direct causal relationship between the service quality on one hand, and students’ satisfaction and academic performance on the other, a mediation model hypothesizes that the service quality causes the mediator variable (attitude toward learning), which in turn causes the dependent variables (students’ satisfaction and academic performance). Having certified the measurement instrument’s suitability for statistical analysis, the structural equation modeling was used to explore the relationship between the variables. Specifically, to ascertain whether attitude towards learning performed any mediating role in the relationship between students’ satisfaction and academic performance. [
Independent variable | Coef. | OIM Std. Err | Z | P > |z| | 95% Conf. | Dependent variable |
---|---|---|---|---|---|---|
HEdPERF | 0.3059591 | 0.0572739 | 5.34 | 0.000 | 0.1937044 | Academic Performance |
HEdPERF | 0.5731455 | 0.0530769 | 10.80 | 0.000 | 0.4691166 | ATL |
HEdPERF | 0.7486839 | 0.05347 | 14.00 | 0.000 | 0.6438845 | Students’ Satisfaction |
ATL | 0.2008102 | 0.438166 | 4.58 | 0.000 | 0.1149312 | Students’ Satisfaction |
ATL | 0.2005642 | 0.0396059 | 5.06 | 0.000 | 0.1229381 | Academic Performance |
ATL = Attitude Towards Learning.
conditions to exist the independent variable should significantly relate to the mediator and the mediator should also significantly relate to the dependent variable. The relationship between the independent variable and dependable variable diminishes when the mediator is in the model. That means that, each of the constructs should show proof of a nonzero monotonic association with each other, but the relationship of the independent variable and dependent variable must decrease substantially upon adding the mediator as a predictor of the dependent variable [
The study expects attitude towards learning to mediate between HEdPERF on one hand and students’ satisfaction and academic performance on the other. Examining the standard estimates of the mediation model, it is observed that the direct paths from HEdPERF to students’ satisfaction is positive and statistically significant (β = 0.7486839; Z = 14.00; P = 0.000). The indirect path of HEdPERF through attitude towards learning to students’ satisfaction is also positive and statistically significant (β = 0.1150935; Z = 4.22; P = 0.000). The total effect for HEdPERF is also positive and statistically significant (β = 0.8637774; Z = 17.85; P = 0.000). As regards the standard estimates of the mediation model between HEdPERF and academic performance, it is observed that the direct paths from HEdPERF to academic performance is positive and statistically significant (β = 3,059,591; Z = 5.34; P = 0.000). The indirect path of HEdPERF through attitude towards learning to academic performance is also positive and statistically significant (β = 0.3247469; Z = 7.54; P = 0.000). The total effect for HEdPERF on academic performance is also positive and statistically significant (β = 630,706; Z = 13.97; P = 0.000). Base on the assumption by [
The implication is that, HEdPERF as a measure of service quality on its own will impact positively and significantly on students’ satisfaction and academic performance. There is also another way that students’ satisfaction and academic performance can be enhanced; thus through students’ attitude towards learning.
HEdPERF which is a measure of service quality positively and significantly
Path | Direct Effect (D) | Indirect Effect (I) | Total Effect (D + I) | Form of Mediation |
---|---|---|---|---|
HEdPERF ATL SAT | 0.7486839** | 0.1150935** | 0.8637774** | Partial |
HEdPERF ATL PERF | 0.3059591** | 0.3247469** | 0.630706** | Partial |
Note: ATL = Attitude towards learning; PERF = Academic Performance; SAT = Students’ Satisfaction; ** = Significant.
predict both students’ satisfaction, academic performance and attitude towards learning and attitude towards learning also positively predicts students’ satisfaction and academic performance. Attitude towards learning partially mediates the relationship between HEdPERF and students’ satisfaction on one hand and HEdPERF and academic performance on the other. This implies that, HEdPERF on its own can impact on students’ satisfaction and academic performance. However, if positive attitude towards learning are intensified, students’ satisfaction and academic performance can also be realized.
This study has the objective to investigate the impact of HEdPERF on students’ satisfaction and academic performance, and the mediating role of students’ attitude towards learning. To achieve this objective, the research appraised all the measurement scales of the said constructs to determine their measurement value in the study context for theory and managerial practices. The study found that out of the HEdPERF 36 variables as developed by [
Hypothesis | Status | |
---|---|---|
H1 | Service quality has positive and significant impact on students’ satisfaction. | Supported |
H2 | Service quality has positive and significant impact on academic performance. | Supported |
H3: | Attitude towards learning positively and significantly affects academic performance. | Supported |
H4: | Attitude towards learning has positive and significant relationship with students’ satisfaction | Supported |
H5a | Attitude towards learning has full mediation effect on the relationship between service quality, and academic performance. | Rejected |
H5b | Attitude towards learning has full mediation effect on the relationship between service quality, and students’ satisfaction | Rejected |
and academic performance. As regards the mediation effect, attitude towards learning partially mediates between HEdPERF on one hand and students’ satisfaction and academic performance on the other. This means that students’ satisfaction and academic performance can be achieved through HEdPERF and/or through attitude towards learning.
The major conclusion from the study is that, for predictive purposes managers of higher education sector should focus on academic aspect, reputation, and programme issues to achieve students’ satisfaction and academic performance. As this study has indicated negative relationship between non-academic aspect on one hand and students’ satisfaction and academic performance on the other, managers of higher education institutions should formulate and implement non-academic policies that aim to improve students’ satisfaction and academic performance. The direct effect of HEdPERF on student’s satisfaction is greater than the indirect effect. This implies that managers of higher education can achieve better students’ satisfaction through service quality than to use service quality to enhance attitude towards learning before improving students’ satisfaction. On the other hand, the indirect effect of HEdPERF on academic performance is greater (β = 0.3247469; 0.000) than the direct effect (β = 0.3059591; 0.000). This means that academic performance can be improved when service quality enhances attitude towards learning.
This research has provided additional insight into HEdPERF, students’ satisfaction, attitude towards learning, and academic performance. The negative relationship between non-academic aspect dimension and students’ satisfaction and academic performance should be further investigated. The partial mediation role of attitude towards learning on the relationship between HEdPERF on one hand and students’ satisfaction and academic performance on the other needs further research in different higher education context. Notwithstanding the new insight into HEdPERF, students’ satisfaction, attitude towards learning and academic performance, caution is needed in generalizing the findings although considerable evidence of relative efficacy has been found in the modified constructs. The present study is limited to Ghanaian Private Universities based in Kumasi and the assertion needs to be validated by further studies in different University settings.
Banahene, S., Kraa, J.J. and Kasu, P.A. (2018) Impact of HEdPERF on Students’ Satisfaction and Academic Performance in Ghanaian Universities; Mediating Role of Attitude towards Learning. Open Journal of Social Sciences, 6, 96-119. https://doi.org/10.4236/jss.2018.65009