MID-TERM ASSIGNMENRT_________________________________

Analyzing the factors affect student satisfaction with dormitory. A case study of International school, Thai Nguyen University

Full name:Nguyn Th Uyn

Eng name:Taylor

ID:IB 2011 - 036

Class :ISIB K1

Teacher:MBA. Quan Thai Ha

Topic:Scientific of writing

Date of submit: April 10, 2015Submitted by: Nguyen Thi Uyen

Table of ContentsBrief introduction3Research questions:4Research objectives:4Conceptual framework:4Chapter 4: Results and discussion54.1 Results54.1.1 Information of respondents64.1.1.2 Factors affecting student satisfaction with the dorm of International school.84.1.3 The relationship between each factor in the model and student satisfaction.214.1.4 The differences about student satisfaction level between groups in demographic information.244.2 Discussion254.2.1 Information of respondents254.2.2 Factors affecting student satisfaction with the dorm of International school.264.2.3 The relationship between each factor in the model and student satisfaction.274.2.4 The differences about student satisfaction level between groups in demographic information.28Appendix29

Brief introductionThis research topic is about analyzing the factors that affect student satisfaction with dormitory: A case study of International school, Thai Nguyen University is an empirical study provides an overview of student dormitory status and the satisfaction level of international school student. Based on the findings, the policy recommendations will be suggested to improve the quality and services of dormitory to meet needs and aspirations of students as well as their parents. To conduct this research, the researcher has set up a conceptual framework to answer all research questions and gain all objectives which were expected. They will be presented below:Research questions: What are factors affecting student satisfaction with the dorm of International school? Is there any relationship between those factors and student satisfaction? What are solutions for improving the service quality of the dorm to improve student satisfaction level?Research objectives: Identify factors that affecting the students satisfaction for the dormitory of International School. Explore the relationship between those factors and student satisfaction. Purpose solutions for improving service quality in the dormitory to improve student satisfaction level.Conceptual framework:This part will provide the conceptual framework by study the period theories of the relationship between satisfaction and quality of service, as well as patterns practical related research in literature review. This section will not only explain the key factors (variables) and the relationship between models, theories that are mentioned in chapter 2 but also draw the way how the researcher will do to conduct this research.

Based on what the researcher has found out of literature review, the relationship between service quality and student satisfaction can be shown in figure 1. The three service quality dimensions have been selected from SERVQUAL model; those are responsiveness, empathy and reliability. By studied the previous theories, there are three more factors have the relationship with student satisfaction: Price, physical facilities and serving capacity. To determine the level of student satisfaction with each factor that was mentioned, the author will test six hypotheses below:H1: Price of the dorm has significant relationship with student satisfaction.H2: Physical facilities of the dorm have significant relationship with student satisfaction.H3: Serving capacity of the dorm has significant relationship with student satisfaction.H4: Responsiveness has significant relationship with student satisfaction.H5: Empathy has significant relationship with student satisfaction.H6: Reliability has significant relationship with student satisfaction.Chapter 4: Results and discussionThis chapter will present the results of research that were conducted based on the methodology described in chapter 3. It includes two main sections. The first section describes a process of analyzing raw data by using some data analysis techniques. The second section shows a detailed discussion of results that the researcher has found. This section will discuss about the meaning of findings which is presented in the first section, the limitation of research and suggestions for further research. 4.1 ResultsResult was get from data analysis process which has described in chapter 3.The structure of this part will be presented according to the research questions/objectives.4.1.1 Information of respondentsThis study was conducted entire population so respondents are all students (k1-k4) who live in the dorm of IS. The researcher has clarified all responses; both of them are suitable with the requirement. The demographic statistics are provided within figure 1, 2, 3 which describe gender, course, and nationality of respondents.4.1.1.1 GenderPie chart above presents the gender of respondent, it can be clearly seen that male only make up 21.88% in total of student; but the amount of female is about three times as the male. To find out more detail, please go to appendix 1 for clear statistic.

Figure 4.1.1.1: Percentage of respondent by gender4.1.1.2 CourseThis pie chart illustrates respondents kind of course in four categories from course1 to course 4. A significant number of students come from course 1 (35.94%). Amount respondents who are students of course 2 and 4 is less than a bit with 21.88%. The lowest percentage of students who response the questionnaire are in course 3 (18.75%).

Figure 4.1.1.2: Percentage of respondents by course

4.1.1.3 NationalityFigure 3 compares the differences of nationality between students in the dorm. The majority of population is Vietnamese, it shows 81.2 percent of respondents are Vietnamese. The dorm includes Pilipino and Lao students because of they are international student who are joining exchange student program .The number of foreigners is approximate 18,7 percent within 12,5 percent of respondents are Pilipino and 6,2 percent are Lao.

Figure 4.1.1.3: Percentage of respondents by nationality4.1.2 Factors affecting student satisfaction with the dorm of International school.Exploratory Factors Analysis (EFA)Exploratory factor analysis (EFA) is used to determine the number of continuous latent variables that are needed to explain the correlations among a set of observed variables.Suitable criteria uses for conducting analysis to explore factors that: Factor Loading > 0.5 0.5 < KMO < 1 Bartlett testing has Sig < 0.05 Total Variance Explained > 50% Eigenvalue > 1 The original model includes 6 factors and 37 items which is expected to effect to student satisfaction with service quality of the dorm. All of 37 items will be used for Exploratory Factors Analysis (EFA) . EFA is conduct by extraction method- Principle Component analysis, varimax method, testing of KMO (KaiserMeyerOlkin) and Bartlett .Table 4.1.2.1: Results of the first time Factors Analysis:Value Comparison

KMO0.5270.550%. This proves that 79.776 % of the data variance is explained by 7 new factors. Factor loading coefficient of all items is > 0.5Testing of Cronbachs alphaUsing Cronbachs alpha to test the reliability of the scales used in the research. Cronbachs Alpha coefficients will use for testing and correlation of total variables.The variable does not guarantee reliable models will be excluded from the study and does not appear when exploratory factor analysis. Criteria for evaluating the reliability of the scales are: Minimum alphais 0.6 Corrected Item-Total Correlation minimum is 0.3.After finish EFA measurement to extract unsuitable items out of the model, the researcher tests the reliability of the scale include seven factor are listed below:1. Serving capacity and empathy2. Physical facilities3. Reliabilities4. Responsiveness5. Service price6. Price 7. Compared priceIn addition, the researcher tests Cronbachs alpha for dependent variable is student satisfaction with the dorm of International School, Thai Nguyen University. Summary table of Cronbachs alpha is presented below:(For more details about result of testing Cronbachs alpha please go to appemdix 5)Table 4.1.2.3: Cronbachs alpha results of dependent and independent variablesNo.Dependent and independent variablesN of itemsCronbachs alphaThe smallest corrected item-total correlation

1Serving capacity and empathy80.9250.671

2Physical facilities

70.8950.559

3Reliability

50.9080.733

4Responsiveness

50.8050.509

5Service price4

0.7130.426

6Price2

0.7820.642

7Compared price2

0.7930.660

8Student satisfaction7

0.8550.326

Through this table of Cronbachs alpha results, all Cronbachs alpha is > 0.6 as well as all Corrected Item-Total Correlation are > 0.3. Hence, the scale of research is reliability enough to conduct.=> Thus, after testing Cronbachs alpha, 33 items appeared after finished EFA are suitable and none of them has to out of the model. Based on EFA and Cronbach testing, research model has to adjust to suitable with following analyzing. Adjusted model is presented in figure 4.2.1 below: In a result, after doing factor analysis process, 33 items are gathered into 7 groups. A table of grouping and naming is set up below:

Table 4.1.2.4: New grouping and naming factor FactorItemsDescriptionGroup name

X1Ser27The protecting employees check the situation of the dorm regularlyServing capacity and empathy

Em29Closing and opening time of the dormitory are reasonable.

Em31You feel comfortable when they are talking with the dorms manager.

Ser28The dorms manager answers students enthusiastically.

Res24 Public services (security, sanitation ...) are guaranteed.

Res23The security situation (theft, fighting, gambling) is solved well.

Ser25The dorm board of management is enthusiastic with work.

Em32The school is always concern about students life.

X2Fac9Room size is large enough for bathroom function. Physical facilities

Fac12Location and hanging area are convenient and spacious.

Fac11Room design ensures for ventilation and lighting.

Fac8Room size is large enough for learning function.

Fac13The dorm was built standard (non-cracked walls, impermeable cap).

Fac16The dorm ensures the requirements of fire prevention.

Fac14Electric and water are provided stability.

X3Reli36Time overcome these problems quickly. Reliability

Reli37You believe in the commitment of the Dormitory staffs

Reli35.When you appeal or complain, the Dormitory resolved quickly and flexibly.

Reli34When facilities (bed, lamps, toilet ...) damaged, the Dormitory keeps timely to repair.

Em33The school listens students idea regularly.

X4Res19Catering services are fit the needs of studentsResponsiveness

Res18Health care for students is always met fully.

Res21The valet parking is safe and spacious.

Res20Refreshment (canteen) is fit the needs of students.

Ser26Canteens staffs are cheerful and friendly.

X5Pri5Prices in canteen at the dorm is suitable.

Service price

Pri6Valet parking prices at the dorm is suitable

Res22The power and water problems are processed quickly.

Fac10The rooms equipment (bed, chair, table, lamp,..) is provided sufficiently.

X6Pri4Water prices at the dorm is suitable.

Price

Pri3Electric prices at the dorm is suitable.

X7Pri2The dorms price is suitable compared to other inn houses.Compared price

Pri1The dorms price is suitable with given service by the school.

Adjusted research model:Adjusted hypotheses:H1: Serving capacity and empathy has significant relationship with student satisfaction.H2: Physical facilities have significant relationship with student satisfaction.H3: Reliability has significant relationship with student satisfaction.H4: Responsiveness has significant relationship with student satisfaction.H5: Service has significant relationship with student satisfaction.H6: Price has significant relationship with student satisfaction.H7: Compared price has significant relationship with student satisfaction.

Correlation coefficient analysisCorrelation is a technique for investigating the relationship between two quantitative, continuous variables. Pearson's correlation coefficient (r) is a measure of the strength of the association between the two variables. However if there is strong correlate between 2 independent variables, it may leads to multicollinearity problem when analyze regression. Study need to consider multicollinearity when doing regression analysis if correlation coefficient >0.3.The meaning of correlation coefficient rr < 0.2 : no correlationr from 0.2 to 0.4 : weak correlationr from 0.4 to 0.6 : average correlationr from 0.6 to 0.8 : strong correlationr from 0.8 to < 1 : very strong correlationThe researcher will create new variables represent for each group of variable (average mean):X1 represents for Ser27, Em29, Em31, Ser28, Res24, Res23, and Ser 25.X2 represents for Fac12, Fac11, Fac8, Fac13, Fac16, and Fac14.X3 represents for Reli36, Reli37, Reli35, Reli34, and Em33.X4 represents for Res19, Res18, Res21, Res20 and Ser26.X5 represents for Pri5, Pri6, Res22 and Fac10.X6 represents for Pri4 and Pri3.X7 represents for Pri2 and Pri1.Unstandardized regression equation of model follows this type:Y = 0+ 1*X1 + 2*X2+3*X3+ 4*X4+ 5*X5 + 6*X6 + 7*X7Result of coefficient correlation analysisCorrelations

X1X2X3X4X5X6Y

serving capacity and empathyphysical facilitiesreliabilityresponsivenessService pricepricestudent satisfaction

X1serving capacity and empathyPearson Correlation1.258*.642**.565**.145.086.677**

Sig. (2-tailed).039.000.000.253.501.000

N64646464646464

X2physical facilitiesPearson Correlation.258*1.396**.078.308*.349**.569**

Sig. (2-tailed).039.001.542.013.005.000

N64646464646464

X3reliabilityPearson Correlation.642**.396**1.439**.337**.348**.797**

Sig. (2-tailed).000.001.000.007.005.000

N64646464646464

X4responsivenessPearson Correlation.565**.078.439**1.282*.118.247*

Sig. (2-tailed).000.542.000.024.353.049

N64646464646464

X5Service pricePearson Correlation.145.308*.337**.282*1.216.346**

Sig. (2-tailed).253.013.007.024.087.005

N64646464646464

X6pricePearson Correlation.086.349**.348**.118.2161.318*

Sig. (2-tailed).501.005.005.353.087.010

N64646464646464

Ystudent satisfactionPearson Correlation.677**.569**.797**.247*.346**.318*1

Sig. (2-tailed).000.000.000.049.005.010

N64646464646464

*. Correlation is significant at the 0.05 level (2-tailed).

**. Correlation is significant at the 0.01 level (2-tailed).

After finished coefficient analysis, factor X7 - compared price does not appear in the model. So after testing correlation coefficient X7 is removed out of the model. All sig. value between independent variables and student satisfaction is 0.6).4.1.3 The relationship between each factor in the model and student satisfaction.Regression analysis The researcher use regression analysis to analyze the relationship between independent variables (6 factors) and dependent variable (student satisfaction) in this part. Regress model will help to describe type of relationship and to predict dependent variable value when independent variables value is known.After testing correlation, X7 was removed out so that he researcher sets up hypothesis to examine the relationship between independent variables and satisfaction (6 hypotheses):Table 4.1.3.1: Hypothesis to test the relationshipHypothesisContent

H1Serving capacity and empathy has no relationship with student satisfaction.

H2Physical facilities have no relationship with student satisfaction.

H3Reliability has no relationship with student satisfaction.

H4Responsiveness has no relationship with student satisfaction.

H5Service price has no relationship with student satisfaction.

H6Price has no relationship with student satisfaction.

Multi-regression analysis will be applied in the model by using enter method Regression analysis resultModelStandardized CoefficientstSig.Collinearity Statistics

BetaToleranceVIF

1(Constant)1.567.123

serving capicity and empathy.4304.911.000.4482.231

physical facilities.2363.451.001.7331.364

reliability.4965.693.000.4522.210

responsiveness-.268-3.583.001.6141.629

Service price.1121.698.095.7871.271

price.034.514.609.7881.269

a. Dependent Variable: student satisfaction

Based on regression table, there are two variables have significant level Sig. (p-value) dont attain significant level 5% =0.05: Service price(X5) = 0.095 and Price(X6) =0.609.So that for all listed hypotheses: Model not rejects H5 and H6, it means Service price and Price dont affect student satisfaction with the dorm of International School.Model rejects H1, H2, H3 and H4, it means Serving capacity and empathy, physical facilities, facility and responsiveness affect student satisfaction with the dorm of International School.After extract two variables has sig. >0.05 (X5 and X6) out of regression model, run model again with variables which are kept and the result is shown below:

ModelStandardized CoefficientstSig.Collinearity Statistics

BetaToleranceVIF

1(Constant)2.467.017

serving capicity and empathy.3914.614.000.4872.053

physical facilities.2724.185.000.8281.207

reliability.5416.577.000.5181.929

responsiveness-.233-3.196.002.6591.517

a. Dependent Variable: student satisfaction

Thus, after regression analysis process, all of variables has suitable significant value (0.0001, and VIF < 10. These variables are suitable in this model, the standardized regression model is presented:Y= 0.391X1 +0.272X2 + 0.541X3 -0.233X4.Table 4.1.3.2: Summary of regression analysis result (more detail in appendix 6)CriteriaValueComparison

R0.891

R Square (R^2)0.793

Adjusted R^20.779

Testing sig. of F0.0000.000 < 0.05

Durbin- Watson coefficient1.7911 < 1.791< 4

Standardized regression model Y= 0.391X1 +0.272X2 + 0.541X3 -0.233X4.

F- test uses in analysis of variance is a method of hypothesis testing about the suitability of multi-regression model. In this case, F has sig. = 0.000 Final standardized regression model of this research: Y= 0.391X1 +0.272X2 + 0.541X3 -0.233X44.1.4 The differences about student satisfaction level between groups in demographic information.ANOVA analysis Analysis of variance Hypothesis H1: There is no difference about satisfaction level between male and female.Hypothesis H2: There is no difference about satisfaction level between different courses.Hypothesis H3: There is no difference about satisfaction level between different countries.To test three hypotheses above, the researcher using ANOVA analysis to test Leneve statistic and the results is listed in appendix 7)For H1: Levene testing shows that significant level sig. of all independent variables in analysis of variance are greater than 0.05 (> 0.05). Therefore, H1 is not rejected; it means there are no differences about satisfaction level between male and female.Result shows that H2, H3 arent rejected, too. It means that students are in any course or come from any country; there are no differences about satisfaction level between them.4.2 DiscussionThis part will provide an overview of what were findings and its meaning in the study by the researcher. Discussion part also helps the researcher make sense for his/her findings for the result and present it logically. This part will be presented follow the order which is written in results part.4.2.1 Information of respondents4.2.1.1 GenderThe result shows that there are more female live in the dorm than male. This may explain based on characteristic of students. Male students have free psychology than female student so they would rather live outside than live in the dorm.4.2.1.2 CourseThe amount of respondents distribute quite steadily in four courses. It may lead a good result in this study because the proportion of respondent divide by course is balance rate.4.2.1.3 NationalityVietnamese student account for a very big proportion of respondents compare to the number of foreign student. This result can completely explain because the amount of foreign students who are exchange student is quite small.4.2.2 Factors affecting student satisfaction with the dorm of International school.EFA was conduct to serves to identify a set oflatent constructs underlying a battery of measured variables. After analyze the result, factors was grouped into 7 new groups. It means suggested model has to adjust for suitable with EFA results.After testing Cronbacks alpha of reliability, all variables are suitable with setting up condition (Cronbachs alpha is > 0.6 as well as all Corrected Item-Total Correlation are > 0.3). It means that the scales used in the research are reliability and standardized. In correlation coefficient analysis (Pearson test), all sig. value between independent variables and student satisfaction is 0.3. ; multicollinearity is a state of very high intercorrelation or inter-associations among the independent variables. It is therefore a type of disturbance in the data, and if present in the data the statistical inferences made about the data may not be reliable.The cause of multicollinearity may come from nature of variables: available relationship between variables in the model. For instance, responsiveness= f( serving capacity and empathy, physical facilities).For further research, to reduce multicollinearity , research can extract variable through 2 steps:Step 1: Test a couple of variables has strong correlationSuppose that X1 has strongly correlate with X2 => Many information about Y belong to X1 also belong to X2 => extract X1 or X2.Step 2: Calculate R square or Standardized R square in regression: For example, R^2 of Y for X1, X2, X3,Xn = 0.978R^2 when extract X1 = 0.899R^2 when extract X2 = 0.911 => extract X24.2.3 The relationship between each factor in the model and student satisfaction.Based on the standardized regression equation that the researcher has founded in regression analysis: Y= 0.391X1 +0.272X2 + 0.541X3 -0.233X4, student satisfaction depends on 4 factors:X1 Service capacity and empathyX2- Physical facilityX3- ReliabilityX4- ResponsivenessBased on regression model, standardize beta coefficients of X1, X2, X3 >0, it means these independent variables have positive relationship with satisfaction. So that when each factor (service capacity and empathy/ physical facilities/ reliability) develops positively, students satisfaction also increases by positive way. By contrast, standardized beta coefficient of X4