Higher Education Marketing Concerns: Factors

Influencing Malaysian Students’ Intention to

Study at Higher Educational Institutions

Master of Business Administration

Lau Sear Haur

( CGA 070099 )

UNIVERSITY OF MALAYA

2009

Higher Education Marketing Concerns: Factors

Influencing Malaysian Students’ Intention to

Study at Higher Educational Institutions

Lau Sear Haur Bachelor of Science (Hons.)

University of Malaya, Malaysia

2006

Master of Science (Distinction)

University of Malaya, Malaysia

2007

Submitted to Graduate School of Business

Faculty of Business and Accountancy

University of Malaya, in partial fulfillment

of the requirement for the Degree of

Master of Business Administration

2009

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ACKNOWLEDGEMENTS

I would like to express my heartfelt thanks to my supervisors, Dr. Yusniza

Binti Kamarulzaman, who has provided me supervision, guidance and advice. This

research project would not have been success without her constant support and

concern. Her trust and patience is very much appreciated.

My special thanks go to Mr. Frankie Lee Chee Lih, Mr. Yong Yuan Wu, Mr.

Chin Kian Hoong, Ms. Ding Kay Lee, Ms. Ng Yin Lee, Mr. Ting Teck Kai, Ms.

Norashikin, and Ms. Lee Wei Ting, who have afforded me advice, help,

encouragement, and suggestion related to this study.

I would like to extend my thanks and appreciation to the supporting staff of

Graduate School of Business (UM-GSB) for the tremendous support given throughout

the entire duration of my research project.

Last but not least, my deepest gratitude also goes to my family numbers, who

were very understanding, and have given their best support and encouragement to me

throughout this study.

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ABSTRACT

Higher education industry in Malaysia has been given a boost in the past couple of

decade. Due to the tremendous increased number of HEI; HE environments have

become intense competitive and HEIs have to compete for recruiting students from

the market. However, with the numbers of HEIs and courses around, it is difficult to

understand how students select HEIs for their choice. Therefore, it is a key issue for

HEI authorities to know what the underlying factors that influencing students’

intention to study at a HEI. The purpose of this research is to assist HEIs’ marketing

effort in understanding of what determines a student’s intention to study at a HEI.

Moreover, the differences among students’ gender and academic background regard

with their perceived important attribute towards HEI are investigated.

A conceptual model integrating the different factors that influencing the study

intention of Malaysian students at a HEI was proposed in this study. The employed

instrument was developed based on adaption from previous studies. The instrument

was then subjected to validity and reliability test to ensure the appropriation. Result

proved that the instrument is appropriate, and applicable in Malaysia context.

A total of 480 pre-university level respondents from Klang Valley were

surveyed in this study. Samples were selected using stratified random sampling.

Findings indicated that the six proposed factors were significant influence on

students’ intention to study at a HEI. Meanwhile findings revealed there were

significant differences among respondents’ gender and their academic backgrounds

on those important attributes towards a HEI. These findings would provide marketers

a comprehensive overview of the different factors that play important roles in

influencing students’ intention to study at a HEI.

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Content Page ACKNOWLEDGEMENTS i

ABSTRACT ii

ABBREVIATIONS vi

LIST OF FIRURE vii

LIST OF TABLE viii

CHAPTER 1 INTRODUCTION

1.1 Introduction 11.2 Education System in Malaysia 31.3 An Overview of the Malaysian Higher Education System 61.4 The Emergence of Marketing in Higher Education Institutions 81.5 Studies of Higher Education Marketing in Malaysia 101.6 Problem Statements 111.7 Research Objectives 131.8 Research Questions 131.9 Scope of the Study 14

1.10 Significance of the Study 141.11 Limitations of the Study 151.12 Organization of the Study 161.13 Conclusion of the Chapter 18

CHAPTER 2 LITERATURES REVIEW

2.1 Introduction 192.2 The Nature of Education as a Service 192.3 Background of the Study 202.4 Colleges and University Selection Process 202.5 Review of Important Attributes 22

2.5.1 Cost of Education 23 2.5.2 Degree (Content and Structure) 24 2.5.3 Physical Aspects, Facilities and Resources 24 2.5.4 Value of Education 26 2.5.5 Institutional Information 27 2.5.6 Significant People (Family, friends, peers and Teachers) 28

2.6 Review of Multiple Attribute Researches 352.7 Gender Effect on HEI Selection 412.8 Academic Background Effect on HEI Selection 432.9 Conclusion of the Chapter 44

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CHAPTER 3 CONCEPTUAL MODEL

3.1 Introduction 453.2 Conceptual Model 453.3 Definition of Variables 483.4 Hypotheses Development 51

3.4.1 Cost of Education 51 3.4.2 Degree (Content and Structure) 51 3.4.3 Physical Aspects, Facilities and Resources 52 3.4.4 Value of Education 53 3.4.5 Institutional Information 53 3.4.6 Influences from People (Family, friends, peers and

Teachers) 54

3.4.7 Gender Differences on Important Attributes of HEI 55 3.4.8 Academic Background Differences on Important

Attributes of HEI 56

3.5 Conclusion of the Chapter 58 CHAPTER 4 RESEARCH METHODOLOGY

4.1 Introduction 594.2 Research Design 594.3 Selection of Sample 594.4 Sampling 604.5 Instrument of Measurement 614.6 Data Collection 624.7 Research Approaches 63

4.7.1 Determination of Sample Normality 63 4.7.2 Descriptive Analyses 64 4.7.3 Validity Test 64 4.7.4 Reliability Test 64 4.7.5 Relationship Approach 65 4.7.6 Differences Approach 65

4.8 Assumptions of the Study 664.9 Conclusion of the Chapter 67

CHAPTER 5 DATA ANALYSIS AND FINDINGS

5.1 Introduction 685.2 Result of Sampling 685.3 Respondents’ Profile 705.4 Normality Test 76

5.4.1 Histogram 76 5.4.2 Stem-and-leaf Plots 76 5.4.3 Boxplot 76 5.4.4 Descriptive Statistic 77 5.4.5 Summary of Normality Tests 77

5.5 Descriptive Analysis

78

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5.6 Validity Test 82 5.6.1 Independent Variables 83 5.6.2 Dependent Variables 90

5.7 Reliability Test 925.8 Correlation Analysis 955.9 Multiple Regression Analysis 97

5.10 Independent Sample t-test 1035.11 One-Way Analysis of Variance (One-Way ANOVA) 1045.12 Conclusion of the Chapter 108

CHAPTER 6 DISCUSSIONS AND CONCLUSION

6.1 Introduction 1096.2 Discussion of Results 109

6.2.1 Normality Tests 109 6.2.2 Descriptive Analysis 109 6.2.3 Validity and Reliability Test 115 6.2.4 Pearson’s Correlation 116 6.2.5 Multiple Regression 116 6.2.6 Independent Sample t-test 118 6.2.7 One-Way ANOVA 119

6.3 Conclusion 1226.4 Implications 1246.5 Recommendations 1266.6 Contribution of the Study 1276.7 Suggestion for Future Research 1286.8 Conclusion of the Chapter 129

REFERENCES 130

APPENDIX I Questionnaire 144

APPENDIX II Figures of Normality Tests 148

APPENDIX III SPSS Analysis Data 159

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ABBREVIATIONS

DV Dependent Variable

etc Et Cetera

H Hypothesis

HE Higher Education

HEI Higher Educational Institution

i.e. In Example

IV Independent Variable

L.O.U. Local Matriculation, Oversea Pre-U and University Foundation Programme

N.A. Not Applicable

NS Not Significant

PHEI Private Higher Educational Institution

Pre-U Pre-university

S.D. Standard Deviation

Sig. Significant

QL Qualitative

QT Quantitative

% Percent

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LIST of FIGURES

Figure 1.1 Flowchart of the education system in Malaysia

Figure 1.2 The organization of the present study

Figure 3.1 A model of international students’ preference by Cubillo et al. (2006)

Figure 3.2 The proposed conceptual model in this study, adapted from Zeithaml

et al. (1996), Joseph and Joseph (1998, 2000), and Cubillo et al.

(2006).

Figure 3.3 The conceptual model and proposed hypotheses in the study

Figure 5.1 The gender group profile of the respondents

Figure 5.2 The age group profile of the respondents

Figure 5.3 The ethnic group profile of the respondents

Figure 5.4 The profile of respondents’ religion

Figure 5.5 The highest qualification status profile of the respondents

Figure 5.6 The family size profile of the respondents

Figure 5.7 The family gross monthly income profile of the respondents

Figure 5.8 Screen plot between eigenvalue and number of factors

Figure 5.9 Screen plot for items in dependent variable

Figure 5.10 Normal P-P Plot of regression standardized residual for dependent

variable

Figure 5.11 The scatter plot of residuals observed value and predicted value

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LIST of TABLES

Table 1.1 Malaysia national education system

Table 1.2 Higher educational institutions in Malaysia

Table 1.3 Student enrolment into HEIs in Malaysia 2002-2007

Table 2.1 Summary of important attributes that affect students’ intention to study at a HEI

Table 2.2 The literature concerning multiple-attributes employed in previous studies

Table 3.1 The definition of each variable in the study

Table 4.1 Purposive sampling and targeted response

Table 4.2 Normality tests employed in this research

Table 4.3 The summary of analysis

Table 5.1 The Detail of Sampling Result

Table 5.2 The Demographical Profiles of the Respondents (N = 480)

Table 5.3 Statistical normality tests for scale data from the sample (N = 480)

Table 5.4 Summary of normality tests of the sample (N = 480)

Table 5.5 Summary of the mean of items according variable (N = 480)

Table 5.6 Summary of the means of computed items according to variable (N = 480)

Table 5.7 The ranking order of each important factor (N = 480)

Table 5.8 The overall score of each factor ranked by respondents (N = 480)

Table 5.9 KMO and Bartlett’s Test for independent variable

Table 5.10 Total variance explained for independent variables

Table 5.11 Output from parallel analysis

Table 5.12 Comparison of eigenvalue from PCA and criterion values from parallel analysis

Table 5.13 Rotation component matrix result for independent variables

Table 5.14 KMO and Bartlett’s Test for dependent variable

Table 5.15 Total variance explained for items in dependent variable

Table 5.16 Component matrix result for dependent variable

Table 5.17 Cronbach’s alpha value of variables

Table 5.18 Inter-Item Correlation Matrix for variable: Cost of Education

Table 5.19 The correlations between the independent variables and the dependent variable (N =480)

Table 5.20 Multiple correlation of independent variables with dependent variable

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Table 5.21 Significances of Independent variables

Table 5.22 Regression coefficients and significance of independent variables

Table 5.23 Independent sample t-test result for male and female respondent towards proposed variables

Table 5.24 One-way ANOVA, F values and effect size

Table 5.25 One-way ANOVA, comparison between groups

Table 5.26 Findings from comparison of groups

Table 6.1 Comparison of ranking order of importance for three distinct nations

Table 6.2 Summary of findings from differential analyses

Table 6.3 Overall result of hypotheses testing

Table 6.4 Overall implication of findings from the present study

CHAPTER 1

Introduction

1.1 Introduction

1.2 Education System in Malaysia

1.3 An Overview of the Malaysian Higher Education System

1.4 The Emergence of Marketing in High Education Institutions

1.5 Studies of Higher Education Marketing in Malaysia

1.6 Problem Statements

1.7 Research Objectives

1.8 Research Questions

1.9 Scope of the Study

1.10 Significance of the Study

1.11 Limitations of the Study

1.12 Organization of the Study

1.13 Conclusion of the Chapter

Chapter 1 Introduction

Chapter 2 Literature Review

Chapter 3 Conceptual Model

Chapter 4 Research Methodology

Chapter 5 Data Analysis and

Findings

Chapter 6 Discussion and

Conclusion

1.1 Introduction 1.2 Education System in Malaysia 1.3 An Overview of the Malaysian

Higher Education System 1.4 The Emergence of Marketing in

High Education Institutions 1.5 Studies of Higher Education

Marketing in Malaysia 1.6 Problem Statements 1.7 Research Objectives 1.8 Research Questions 1.9 Scope of the Study 1.10 Significance of the Study 1.11 Limitations of the Study 1.12 Organization of the Study 1.13 Conclusion of the Chapter

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CHAPTER 1 INTRODUCTION

1.1 Introduction

Education is a growing industry and one where Malaysia is gaining acceptance as a

reputable study destination in the region. The education sector offers a variety of

higher educational programmes as well as professional and specialised skill courses

that are comparatively priced and of excellent quality. In fact, the Malaysian

government has policies to encourage both public higher education institutions (HEIs)

and private higher education institution (PHEIs) to become involved in the provision

of tertiary education and, indeed, has ambitions for establishing Malaysia as a

regional hub for education in South East Asia (David and Anne, 2007). Consequently,

a number of HEIs were established in Malaysia within the last two decades.

A market-sensitive educational system is evolving in Malaysia. Traditionally,

public universities were responsible for providing undergraduate and graduate studies.

While private colleges have been in existence in Malaysia for a couple of decades, the

government has been actively supporting them since 1995 to develop their own

unique and innovative higher education systems. In turn, the higher education (HE)

environment has become increasingly competitive and institutions have to compete

for the recruitment of students in the market. With the introduction of student fees, it

is potential applicants to higher education that have become increasingly consumerist.

As a result, the changes that have occurred in the education sector in Malaysia over

the past few years have aimed at introducing efficiency and competition into this

industry.

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Furthermore, as competition for students intensifies, private universities and

private colleges of higher education have been very aggressive and creative in the use

of marketing approaches and techniques to recruit and attract students. HEI marketers

argue that knowing the reasons applicants choose universities and courses of study is

central to developing institutional positioning in an increasingly competitive HE

environment.

As a matter of fact, students entering institutions of higher education today are

very different than those of previous generations (Abrahamson, 2000). When making

decisions about attending college, and ultimately which college to attend, they

consider factors differently than previous generations. Therefore, from time to time,

HEI marketers need to study the underlying factors that affect students’ HEI choice.

Moreover, the study of choice and decision making in HE is an area of growing

research interest, primarily because HE has been transformed from a domesticated,

centrally funded non marketised entity to a highly marketised and competitive

environment (Soutar and Turner, 2002).

In summary, this study aims to identify the important factors that significantly

influence students’ intention to study at a HEI. Moreover, the differences among

students’ gender and academic background with regard to their perception of

important attributes towards HEIs are investigated. The findings of this study will be

beneficial in terms of decision making and contribute to the roles that assist the HEI

marketers to plan and improve their marketing strategy for the recruitment of

students.

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1.2 Education System in Malaysia

In Malaysia education is the responsibility of the federal government. The national

education system encompasses education from pre-school to university. Pre-tertiary

education (i.e. from pre-school to secondary education) is under the jurisdiction of the

Ministry of Education (MOE) while tertiary education is the responsibility of the

Ministry of Higher Education (MOHE).

Generally, the Malaysian education system provides eleven years of basic

education to every child in the country. Both public and privately funded educational

institutions at all levels of education exist in the national education system. The

educational structure is 6-3-2, that is, six years of primary education, three years of

lower secondary education, and two years of upper secondary education. Primary

education and secondary education are free in public school due to full subsidization

by the Malaysian government. Over 95% of primary and secondary education for

Malaysian children is provided by public schools. The admission age to the first year

of primary education is seven. Primary schooling is mandatory for all children

between the ages of seven and twelve. Students sit for common public examinations

at the end of primary (UPSR), lower secondary (PMR) and upper secondary levels

(SPM). In short, Malaysia has been striving towards universal primary and secondary

education since its independence (Molly, 1999).

While in the past, the education system only provided for nine years of basic

education, a reform in the early 1990s extended the basic education from nine years to

eleven years. Instead of sitting for a selective public examination at the end of the

lower secondary level (i.e., Form 3) with only about 50% of the Form 3 students

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proceeding to Form 4, today all Form 3 students are promoted to Form 4. This has

changed an elitist school system into a system that provides for mass education

(Molly, 2004). The successful democratisation of secondary education has resulted in

an increasing demand for post-secondary education, which, in turn, has brought about

a rapid expansion of higher education as reflected in the increased number of

universities and the proliferation of private colleges.

Furthermore, upon completion of secondary education, students interested in

continuing their study may opt to pursue one to two years of post-secondary

education, which is the university entrance preparatory course (also called pre-

university programme). Examples of pre-university programmes are STPM, GCE A-

level, Local Matriculation, Canadian Pre-University, South Australia Matriculation,

etc. After the completion of pre-university level education, students are eligible to

further their study at the tertiary education level.

At the tertiary education level, institutions of higher learning offer courses

leading to the award of Certificate, Diploma, Degree and postgraduate qualifications.

Certificate, Diploma, Degree, Higher Degree programmes (in academic and

professional fields) are adequately provided for by both the public and private

education sectors. Therefore, at this level, students have several choices for furthering

their studies. As far as higher education marketing is concerned, there is a market for

HEIs and the reasons behind students’ preferences of HEIs have been studied in

previous researches.

Generally, the Malaysian national education system is summarized in Table

1.1 and Figure 1.1.

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Table 1.1: Malaysia national education system

Education Level Starting Age Duration Pre-school Five Two years Primary Seven Six years Lower secondary Thirteen Three years Upper secondary Sixteen Two years Post-secondary Eighteen One to two years Tertiary Twenty Three to five years Post-graduate (Master or PhD) - One to five years

STPM GCE A-Level MatriculationUniversity

Foundation Year

Overseas Pre-U (CPU, SAM)

Pre-Secondary

Primary Education

Secondary Education (Five Years)

(Six Years)

(One Year)

Pre-school education

Tertiary Education

CompulsoryEducation

Figure 1.1: Flowchart of the education system in Malaysia

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1.3 An Overview of the Malaysian Higher Education System

In the early 1990s, there were approximately 200 private colleges, seven public

universities and no private universities in Malaysia. With the nation’s focus on the

development of HEIs, by the end of 2001 there were eleven public universities, five

conventional private universities, and branch campuses of three foreign universities.

By 2005, Malaysia had approximately 72 public and 559 private institutions.

Currently, the number of tertiary education institutions has further increased. There

are now 79 public tertiary education institutions, which comprises 20 universities, 22

polytechnics, and 37 community colleges. Furthermore, at the time of this study there

were approximately 600 PHEIs in Malaysia. The statistics for HEIs is shown in Table

1.2.

Table 1.2: Higher educational institutions in Malaysia

Year Institution 2000 2005 2007

Public University 11 18 20 Polytechnic 11 20 22 Community College 0 34 37 Sub-total 22 72 79 Private University 5 22 32 Branch Campus 3 5 5 College 482 532 563* Sub-total 512 559 600 Total 534 631 679

*Approximation (Source: www.mohe.gov.my, accessed 2 Feb 2009)

As the statistics in Table 1.1 show the number of HEIs in Malaysia has

dramatically increased within the last decade, similarly the enrolment of students into

HEIs in Malaysia has also increased. In 2002, there were 253,153 students enrolled

into HEIs. The number increased to 336,845 by 2007 with a compounded annual

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growth rate (CAGR) of 6.9%. The statistics for student enrolment are presented in

Table 1.3.

Table 1.3: Student enrolment into HEIs in Malaysia 2002-2007

Year Institution 2002 2003 2004 2005 2006 2007

CAGR(%)

Public 87,390 98,781 113,827 117,797 130,771 169,057 14.4 Private 165,763 163,480 169,834 113,105 144,775 167,788 2.6 Total 253,153 262,261 283,661 230,902 275,546 336,845 6.9

Despite the increasing trend of student enrolment into HEIs, a noticeable

pressure is being faced by the HEIs. It has become more difficult to recruit an

adequate number of students due to the increased competition, especially for PHEIs.

The competition has become intensified as many private colleges have forged various

kinds of institutional linkages with foreign universities to offer different types of

degree programmes and professional qualifications. Recently, this practice was

extended to include institutional linkages between private colleges and local public

universities.

Programmes that are linked with foreign universities are sometimes known as

transnational education programmes and these include twinning programmes, credit

transfer programmes, external degree programmes and distance learning programmes.

The twinning programmes are split degree programmes where the students study part

of the degree programme in a local institution before proceeding to the foreign

university to complete the programme. Typical twinning arrangements are either

“2+1” (2 years in a local college and 1 year in an overseas twinning university) or

“2+2”. However, a number of private colleges began to offer “3+0” programmes

when the economic crisis hit Malaysia in 1997 as fewer students could afford to

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continue their studies overseas due to the devaluation of the Malaysian Ringgit.

Currently, there are more than 12 private colleges offering “3+0” programmes and

five branch campuses of foreign universities, which means that Malaysians can obtain

a foreign degree without having to go abroad (Molly, 2004).

Furthermore, as tuition fees are the main source of revenue for most PHEIs,

their programmes have to be tailored to meet the market demand. As a result, the

PHEIs tend to offer programmes in disciplines that do not require a large capital

outlay such as accountancy, business studies, and computer studies. In order words,

the majority of PHEIs in Malaysia offer similar programmes. Consequently, it further

stimulates the competition among PHEIs as well as public HEIs.

1.4 The Emergence of Marketing in Higher Education Institutions

Most HEIs now recognise that they need to market themselves in a climate of

competition, which for universities is frequently a global one, and substantial

literature on the transfer of the practices and concepts of marketing from other sectors

to HE has been developed (Gibbs, 2002). For example, Nguyen and LeBlanc (2001)

focused on the image and reputation of the institution and referred to the crucial role

these factors played in the development of market positioning – they drew on the well

established concepts and theories in business sector marketing for their study. On the

other hand, Binsardi and Ekwulugo (2003), who claimed that “a centrally important

principle of marketing is that all marketing activities should be geared towards the

customer”, relied on the literature used in business sector marketing, and applied it in

the context of higher education.

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Kotler and Fox (1985) provided a definition of education marketing as early as

1985, stating that marketing in the context of education was: “the analysis, planning,

implementation and control of carefully formulated programmes designed to bring

about voluntary exchanges of values with a target market to achieve organisational

objectives”.

Some of the earlier definitions concentrated on “product marketing”, for

example, Kotler and Fox’s (1985) definition stated that students were the “product”

and employers were the customers, Levitt (1980) also viewed a university’s offerings

as products (Binsardi and Ekwulugo, 2003). Later in the 1990s higher education

marketing was defined within the services marketing definition, for example,

Mazzarol (1998) highlighted the key characteristics that provide services marketing

based on the nature of the services using a theory developed by well-established

researchers in business management (Zeithaml et al., 1985; Parasuraman et al., 2004).

The recognition that HE is a service industry further shows that some authors in the

field were anxious to ensure that HE is recognised as a business: a service sector

business.

In contrast, Ogbuehi and Rogers (1990) cited that American universities have

been forced to pay more attention to the utilization of marketing techniques in their

recruitment processes due to the sharp decrease in the number of US High School

graduates. This rationale is increasingly apparent within the Asian region. In the past,

due to the relatively low participation rates in university education and the largely

public provision of such education, Asian Universities tended to have a captive

audience, requiring very little in the way of marketing. However, in recent years,

participation rates have exploded and many private institutions have emerged. This

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means that Asian tertiary institutions need to give close attention to the utilization of

marketing techniques and improving student recruitment.

1.5 Studies of Higher Education Marketing in Malaysia

Studies relating to the marketing of HEIs in Malaysia are relatively few. Nonetheless,

a number of studies have been conducted by many researchers on the institutional

characteristics influencing the choice of institutions in various host countries,

including regions close to Malaysia. Most studies identified the factors that influence

the students’ choice of institutions, however, studies such as Lin (1997), Joseph and

Joseph (1998), Joseph and Joseph (2000), AEI-International Education Network

(2003), Sidin et al. (2003) and Gray et al. (2003) analyze further the underlying

factors of the many variables.

From the existing literature at least six variables can be identified, (1) financial

attractiveness, (2) programme and course suitability and availability, (3) ease and

flexibility of enrolment procedure, (4) future ease of employment after graduating, (5)

attractiveness of institutions, and (6) quality reputation, which have been adopted as

the basis of the hypotheses in this research. In addition, the outcome of the focus

group of an extended study done by Krishnan and Nurtjihjia (2007) revealed that 32

variables should be used instead of 26 variables. However, the research field of higher

education marketing in Malaysia is still at a relatively pioneer stage with much

research still to be carried out both from an exploratory and strategic perspective.

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1.6 Problem Statements

In Malaysia today there is greater opportunity for secondary school students to attend

colleges and universities. Moreover, students are able to select their preference from a

large pool of universities and colleges regardless of whether they are public or private,

or local or overseas HEIs. Consequently, the competition for HEIs to recruit more

students and retain them has become fiercer than ever before (Sohail et al., 2003).

Facing a growing competitive environment, HEIs have dramatically increased the

competition for recruiting and retaining students by providing a high quality service

as the solution to compete in this turbulent market. Due to the increasing competitive

forces for marketing education in Malaysia, marketers need to be more aware of the

underlying factors considered by students when selecting a HEI (Hassan and Sheriff,

2006) if they want to survive in this competitive environment (Vaira, 2004). Thus, it

is very important for marketers to know the factors that influence the study intention

of prospective students and to understand the nature of the relationship among them.

These factors are significant from the perspective of the HEIs marketing strategy

planning for student recruitment. As a result, an extensive investigation of the

important attributes that influence Malaysian students’ intention to study at a HEI is

proposed in this study.

Furthermore, although previous researchers identified many attributes that

influenced students’ choice of institutions, the attributes that distinguish competing

services from one another have not been clearly described. In other words, the

determinant attributes that cause students to choose to attend a particular HEI are

undetermined. Determinant attributes are referred to some way may down the list of

service characteristics that are important to purchasers/students, but they are the

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distinguishing attributes that allow customers/students to differentiate between the

competing alternatives (Lovelock, 2007). It is typical for HEI marketers to identify

the determinant attributes that motivate students to attend a HEI as these determinant

attributes are the essence for HEI marketers to gain a competitive advantage in their

crafting strategies for student recruitment.

In the empirical search process in this study, no studies were found that

address the difference by students’ gender with regard to the choice of HEI in

Malaysia. Previous studies have demonstrated that the gender effect plays an

important role in HEI student recruitment (Shank and Beasley, 1998; Mansfield and

Warwick, 2005). Researchers argue that male and female students differ in the

selection criteria they consider important when choosing a HEI. Thus, it will be

interesting to see whether such gender differences also arise within the Malaysian HEI

context.

Furthermore, few studies were found that investigate the difference by

students’ academic background (especially at pre-university level) towards their

perceived important attributes of a HEI. Elizabeth Ng (2003) observed that students

who studied in different programmes at pre-university level had different preferences

concerning HEIs when studying abroad. The student’s decision in the selection of a

pre-university programme is often associated with a predisposition to attend a HEI in

the near future. Hence, it will be topical to find out whether such academic

background differences arise in the Malaysian HEI context.

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1.7 Research Objectives

In line with the problem statements, this study has two specific objectives

1. To determine and understand the factors influencing students’ intention to

further their study at a HEI

2. To identify the significant differences between students’ gender and academic

backgrounds concerning factors they perceive as important when selecting a

HEI to attend.

1.8 Research Questions

The following research questions were developed in order to guide the present study:

Q1: What are the influencing factors and the contributions they make to a students’

intention to study at a HEI ?

The purpose of this research question is to identify and determine the

important factors (i.e. cost of education, degree (content and structure),

physical aspect and facilities, value of education, institutional information, and

people (family, friends, peers and teachers)) that affect a students’ intention to

study at a HEI.

Q2: How students of different genders and from different academic backgrounds

differ in the selection criteria they consider important when choosing a HEI ?

The purpose of this research question is to identify the differences between

students’ gender and respective academic backgrounds on proposed factors

that affect their intention to study at a particular HEI.

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1.9 Scope of the Study

The scope of this study is limited to those students who live in the Klang Valley. This

is because most of the PHEIs that conduct pre-university courses are concentrated

around major urban areas in the Klang Valley. Moreover, the number of public

schools that offer Form Six (STPM) in these areas is higher than other states. As a

result, a sample from this segment may be considered to adequately represent the

actual population.

Students who are currently attending pre-university level programmes, such as

Form Six (STPM), GCE A-Level, local matriculation, overseas Pre-U courses, and

other foundation courses are defined as the target sample in this study. The targeted

sample is defined as such due to this group of people having the highest possibility of

furthering their studies in HEIs in the near future. To a certain extent they are of

interest to HEI marketers in order to determine the factors that can alter a student’s

choice of HEI.

1.10 Significance of the Study

The findings of the research would expound on the theoretical contributions, thus,

enriching the existing literature. This research will explain further those factors that

influence a students’ intention to study at a HEI.

The findings of this research will be beneficial to both students (customers),

and institutions (service providers) for better future planning and decision making.

Moreover, the results of this research will provide HEI marketers with a better view

of the important factors that students consider in their selection of a HEI. Hence, HEI

marketers may gain a better understanding of the actual needs and perceptions of

15

students in their further study decision making process. In consequence, HEIs may

improve their marketing strategy in student recruitment.

1.11 Limitations of the Study

The sampling process of the present study was carried out in the Klang Valley. Even

though the majority of educational institutions that offer pre-university programmes

are concentrated in this urbanized area, there are some others located in Suburban

areas of Malaysia. For instance, public high schools that offer Form Six programmes.

Thus, samples from the Klang Valley may not be adequate in generating an

exhaustive picture that reflects the whole student population in Malaysia.

Furthermore, students from sub-urban areas may have distinct preferences concerning

HEIs compared to students who live in urban areas.

Also, the accessibility of respondents to the questions in the questionnaire

remains unknown. This study applied a quantitative approach; the instrument was

developed by adapting a few sets of established questionnaires from previous studies.

To a certain extent, evaluations made by respondents may not be accurate due to gaps

or misunderstandings between the respondents’ and the concepts measured by the

question. Moreover, the honesty of respondents in answering the questions during the

survey is a constraint of this study.

16

1.12 Organization of the Study

This thesis consists of six chapters and the organization of the study is as follows:

Chapter 1: This chapter presents the introduction, related information on the interests

of study, problem statements, research objectives, research questions,

research scope, and significance and limitations of study.

Chapter 2: This chapter addresses the nature of education as a service, the background

of the study, college and university selection process, comprehensive

review of important attributes and multiple attribute researches, and gender

and academic background effects on HEI selection.

Chapter 3: This chapter focuses on the development of the conceptual model,

definition of proposed variables, and hypotheses development.

Chapter 4: this chapter covers the selection of the sample, sampling technique,

instrument design, data collection process, extensive research approach

and research methodology employed in this study, and assumptions of the

study.

Chapter 5: This chapter presents the sampling results and respondents’ profile, data

analysis and findings from various analyses such as normality tests,

validity and reliability tests, Pearson’s correlation, multiple linear

regression, independent sample t-test, and One-way ANOVA.

Chapter 6: This chapter includes an in depth discussion of the results, conclusion,

implications, recommendations, contribution of the study, and suggestions

for future research.

The organization of this study is graphically presented in Figure 1.2.

17

Figure 1.2: The organization of the present study

Chapter 1 Introduction

Chapter 2 Literature Review

Chapter 3 Conceptual Model

Chapter 4 Research Methodology

Chapter 5 Data Analysis and

Findings

Chapter 6 Discussion and

Conclusion

18

1.13 Conclusion of the Chapter

This chapter described the general view of the present study. Information relating to

the interest of the study was discussed. The problem statement, research objectives,

and research questions were clearly defined. Further, the scope and significance of the

study were covered. Limitations of the study were stated, and the chapter ended with

the organization of the study. The literature regarding this study is reviewed in

Chapter 2.

CHAPTER 2

Literature Review

2.1 Introduction

2.2 The Nature of Education as a Service

2.3 Background of the Study

2.4 Colleges and University Selection Process

2.5 Review of Important Attributes

2.5.1 Cost of Education

2.5.2 Degree (Content and Structure)

2.5.3 Physical Aspects, Facilities and Resources

2.5.4 Value of Education

2.5.5 Institutional Information

2.5.6 Significant People (Family, friends, peers and Teachers)

2.6 Review of Multiple Attribute Researches

2.7 Gender Effect on HEI Selection

2.8 Academic Background Effect on HEI Selection

2.9 Conclusion of the Chapter

Chapter 1 Introduction

Chapter 2 Literature Review

Chapter 3 Conceptual Model

Chapter 4 Research Methodology

Chapter 5 Data Analysis and

Findings

Chapter 6 Discussion and

Conclusion

2.1 Introduction 2.2 The Nature of Education as a Service 2.3 Background of the Study 2.4 Colleges and University Selection

Process 2.5 Review of Important Attributes 2.6 Review of Multiple Attribute

Researches 2.7 Gender Effect on HEI Selection 2.8 Academic Background Effect on HEI

Selection 2.9 Conclusion of the Chapter

19

CHAPTER 2 LITERATURE REVIEW

2.1 Introduction

This chapter presents an extensive review of the literature and research related to

factors that influence a students’ intention to study at a HEI. This chapter first

discusses the nature of education as a service industry. The second part focuses on the

background of the study, followed by stages in the college or university selection

process. Moreover, this chapter describes literature concerning the important

attributes, multiple-attribute researches, gender, and academic background effects on

HEI selection. This chapter ends with a discussion on marketing in higher education.

2.2 The Nature of Education as a Service

Services present special characteristics that require a particular marketing strategy

application (Stanton, 1974; Andreson et al., 1993; Kotler et al., 1995). By their

nature, services cannot be touched, tasted, or possessed (Dawidow et al., 1989). In

general, services are intangible, heterogeneous, perishable, and require simultaneous

production and consumption (Zeithaml et al., 1985; Ahmed et al., 2002).

Students usually associate intangibility with a high level of risk. Thus,

intangibility hinders the communication of services to the customer (Rathmell, 1966)

and the setting of prices for international education (Mazzarol, 1998). Consequently,

the decision process of consumers is influenced by indirect mechanisms of service

evaluation. Students evaluate these aspects based on the image of the brand, the

institution, and the country of destination.

20

Higher education is a pure service and is characterized by a greater amount of

interpersonal contact, complexity, divergence, and customization compared to other

service businesses (Patterson et al., 1998). Most of the quality attributes in higher

education cannot be perceived, felt, or tested in advance. This nature brings

difficulties to the evaluation of a programme, especially for an international student

(Harvey and Busher, 1996; Patterson et al., 1998; Srikatanyoo and Gnoth, 2002).

2.3 Background of the Study

Researchers have focused on student choice of college or HEI for more than 40 years.

In the 1960s and 1970s, this research related to sociology, which explored the process

of social mobility and occupational attainment (Sewell & Shah, 1968; Alexander &

Eckland, 1975). Other researchers, such as Lewis and Morrison (1975), examined

college choice as complex decision-making. In the 1980s and 1990s, most college-

choice research focused on three basic studies: factors influencing college choice,

stage models, and student (as consumer) behaviour. In this case, the proposed

research in this study is one of the analyses towards factors influencing students’

intention to study at a HEI. Nevertheless, the stage model is discussed in the next

section for a better understanding that will complement the implications of this study.

2.4 College and University Selection Process

Choosing a college or university is a critical stage for all high school graduates who

plan to attain higher education in the future. However, students may make decisions

that will affect persistence, which is a critical stage in their education.

The literature on student college choice suggests a three-stage process for

decisions to select a HEI (Jackson 1982; Litten 1982; Chapman 1984; Hossler and

21

Gallagher 1987; Hossler et al., 1989). Hossler and Gallagher (1987) proposed a three

phase model of college choice. At each phase of the model, individual and

organizational factors interact to produce outcomes that influence the student college

choice process as follows:

The first stage is the predisposition phase in which students determine whether

they would like to continue their education beyond the secondary level or not. This

phase is affected by student ability, achievement, socioeconomic status, parents, peer,

educational activities and school characteristics (Tillery, 1973; Litten, 1982; Stage

and Hossler, 1989; Nora and Cabrera, 1992; Somers et al., 1999).

The second stage is the search phase during which they gather information

about institutions of higher education and formulate a choice set that is the group of

institutions to which they will actually apply. The search phase is affected by the

students’ preliminary HEI values, their search activities and college or university

search activities for students (Chapman, 1981; Hossler and Gallagher, 1987).

The third stage is that of choice, that is, deciding which college or university

to actually attend. Educational and occupational aspirations, costs and financial aid,

and college or university courtship activities influence the choice phase (Hossler and

Gallagher, 1987; John, 1990; Nora and Cabrera, 1992).

According to the literature, there are many attributes affecting a students’

choice decision making, especially at the second and the third stage. It is known that

physical characteristics, personal influences, costs and financial aids and academic

and social variables influence the students’ choice and persistence towards a HEI

(Hossler, et al. 1989: Bean, 1990; Paulsen, 1990; Cabrera et al., 1992).

22

The purpose of this study is to investigate students’ perceived important

attributes during the university choice process, and whether there are significant

differences between student’s gender and course of study during their pre-university

level (academic background). This information is vital to HEI marketers as

understanding the factors affecting students’ choice and persistence will enable HEI

marketers to influence students’ decisions towards choosing their college or

university. Hence, it provides significant insights that allow HEI marketers to gain a

competitive advantage over their competitors.

2.5 Review of Important Attributes

Higher education is not a frequent purchase and demands a high level of involvement

from students (Brookes, 2003). Indeed, the decision to study at a HEI involves cost

(time and monetary) and people surrounding the student. Moreover, as discussed in

Section 2.2, education is one kind of service that cannot be easily touched and tasted.

The only way to evaluate the appropriateness of the choice to study at a HEI is to go

through the process by experience. In turn, the perceived risk of making a decision of

HEI choice is relatively high.

Therefore, in order to determine their preferences, prospective students

consider what is important for them, and then generate a conscious/unconscious trade-

off among the attributes (Soutar and Turner, 2002). In fact, a number of researches

were carried out to study the important attributes that influence students’ study

intention. In this study, attention was given to six important attributes.

23

2.5.1 Cost of Education

Tillery and Kildergaard (1973) stated that cost is more influential concerning whether

a student attends college or not than it is on which college he or she attends. Cabrera

and La Nasa (2000) pointed to research that consistently showed a significant

negative relationship between tuition increases and enrolment. Besides, in the

research done by Leslie and Brinkman (1988), findings suggest that all students were

sensitive to tuition cost.

According to research done by Hossler et al. (1989) 70% of students and 87%

of parents indicated that they were either “well informed” or “informed” about

financial aid programmes and their eligibility for financial aid. Some theorists cited

that receiving aid is more important than the amount of aid received, because that aid

becomes the substantive way the institutions communicate that “we want you to be

part of our community” (Jackson, 1982; Abrahamson & Hossler, 1990; Freeman,

1997).

In contrast, Hossler et al. (1998) concluded that parents’ willingness to

contribute, regardless of family income, has some effect on tuition and financial aid

sensitivity. Their research also concluded that for Asian students, financial aid offers a

vehicle in attracting them to specific institutions.

Foskett et al. (2006) found that flexibility of fee payment, availability of

financial aid, and reasonable accommodation costs in that order exert a significant

influence on students’ choice of HEI.

24

2.5.2 Degree (Content and Structure)

Hooley and Lynch (1981) observed that the suitability of the programme is the most

important factor, as students will accept any level of the other factors. Studies that

focused on the variables that influence students’ selection of tertiary institution

(Houston, 1979; Krone et al., 1983; Webb, 1993) point towards a wide range of

choice criteria. The criteria that seem to be most important are programme related

issues such as flexibility and length of the programme, and programme entry

requirements. Houston (1979) found length of the programme was at the bottom of

the scale, while in Webb’s (1993) study it is one of the most important elements.

Krampf and Heinlein (1981) found that prospective students compare

programmes offered with those promoted by competing institutions in order to check

their suitability. The elements that influence the programme evaluation are: the

selection of courses (Qureshi, 1995), their quality (Turner, 1998), availability of

courses, and entry requirements (Bourke, 2000).

The availability of majors is one of the primary considerations shaping actual

matriculation (Choy and Ottinger 1998; Hossler et al., 1999). Also, Brennan (2001)

stated that admission criteria as a proxy for quality is potentially more important than

the programme offering. Programme evaluation is conceptualised as the consumers’

attitude towards targeted programmes (Peng et al., 2000).

2.5.3 Physical Aspects, Facilities and Resources

Chapman (1984) cited that fixed college characteristics are one of the external

influences that influence a student’s intention to study at a particular HEI. The fixed

25

characteristics comprising college size, campus environment and good quality of

faculty members are for the most part under the control of the institution.

Researchers such as Litten (1980), Tierney (1983), and Seneca and Taussig

(1987) found that academically-talented students look for different attributes

compared to average students. The former evaluate an institution based on the quality

of their programmes while the latter, in addition to good programmes, are also

interested in factors like physical appearance and social life. This illustrates the scope

for segmenting the market and approaching the recruitment of the distinct segments

with tailor-made strategies.

Jackson (1982) stated that most students only seriously consider colleges

located relatively near their homes that present no extraordinary financial or academic

obstacles.

Wajeed and Micceri (1997) identified that the location of the HEI has a

significant influence on the college choice of high school students. Their research at

the University of South Florida (USF) suggested that geographic location or

proximity is a primary motivating factor for students choosing to attend USF. They

concluded that First Time in College (FTIC) and students from community colleges

show enrolment preferences for institutions in their home counties or regions.

Past studies pointed out that HEI selection is determined by several factors

including the quality and expertise of its teaching faculty, attractiveness and campus

atmosphere (Krampf and Heinlein, 1981; Lin, 1997; Mazzarol, 1998; Soutar and

Turner, 2002).

26

The physical environment of the service production constitutes an important

element in the decision-making process. Price et al. (2003) found that when provided

with a high standard, facilities are considered as a relevant factor in influencing the

students’ selection of the institution in which they will pursue their studies.

The output of Price et al. (2003) analyses the degree to which facilities and

location factors influence the decision of a group of customers. The most important

factor related to facilities is social life at the university and its surroundings. Results

also revealed that factors such as safety, security, cleanliness, and sports facilities are

considered less significant.

Other physical factors influencing the students’ HEI choice through auxiliary

services are: library facilities (Qureshi, 1995), availability of computers, quality of

library facilities, availability of quiet areas such as study rooms, and the availability of

areas for self-study (Price et al., 2003).

2.5.4 Value of Education

The academic reputation and image of the institution are the sum of opinions, ideas,

and impressions that prospective students have of the institution (Kotler and Fox,

1995). Their opinion about the reputation and image of the institution are formed from

word of mouth, past experience, and marketing activities of the institution (Ivy, 2001).

Thus, very often the perception of the institution’s excellence goes beyond its actual

quality (Kotler and Fox, 1995).

27

Increasingly, students are becoming extremely critical and analytical when

choosing their educational institutions (Binsardi and Ekwulugo, 2003). Due to the

growing competence in international education, HEIs need to maintain and develop a

distinctive image in order to reach a competitive advantage (Paramewaran and

Glowacka, 1995). In this way, the quality of reputation and branding are two

important sources for this purpose (Hall, 1993; Qureshi, 1995; Mazzarol, 1998;

Bourke, 2000).

A positive image can strongly influence the decision to attend an educational

institution (Krampf and Heinlein, 1981; Qureshi, 1995; Mazzarol, 1998; Bourke,

2000; Gutman and Miaoulis, 2003). The institution selection is determined by several

factors such as the academic reputation and prestige of the institution (Krampf and

Heinlein, 1981; Lin, 1997; Mazzarol, 1998; Soutar and Turner, 2002). Prospective

students also consider the positioning of the institution within the ranking of academic

organizations.

2.5.5 Institutional Information

Cleopatra (2004) cited that in order to increase participation and to assist students in

their choice of institution, information is needed that will change the attitude of the

potential students and facilitate their decision-making. Moreover, due to the highly

competitive HEI market, facing concerns relating to widening access, and students

facing new choices and many more alternatives, produce and seek increased

information to enable them to reach an informed and better decision. Applicants

information seeking continues even after students’ initial selection of institutions and

the completion of their post-secondary form or pre-university level (Moogan et al.,

1999).

28

Furthermore, Cleopatra (2004) identified that information regarding career

prospects and area of study for a course were significantly important to students in the

study. Career prospects information such as the average earnings of the graduates and

the percentage of graduates who are employed within a year of their graduation; area

of study referred to the content of a specific course and the course as a learning

experience.

Joseph and Joseph (1998, 2000) reported that the course and career

information is, by far, the most important category of information during the selection

of a specific higher education institution. Studies found that potential students place a

strong emphasis on the need to collect, and no doubt compare, academic information

such as area of study, and career opportunities after graduation (Cleopatra, 2004;

Felix, 2006).

2.5.6 Significant People (Family, friends, peers and Teachers)

Studies of the college and university choice process have shown that a person’s

decision to attend college is influenced by individuals with personal or social ties to

the student. Sheppard et al. (1992) showed that parents, other family members, and, to

a lesser extent, peers had the largest influence on students’ college aspirations.

Chapman’s model includes the influence of high school personnel as an additional

significant person in a student’s college choice process.

Research done by Hossler et al. (1999) on significant persons to student

college choice indicated that by the junior year, the search activities of the students

rose dramatically from their sophomore year. The study showed that 43% of

29

respondents reported that they spoke with friends, teachers, counsellors, or parents

about college. Another 61% obtained information from counsellors and local libraries.

In addition, 55% sent off for college information and 55 % visited one or more

campuses. Consequently, by the end of the junior year, teachers and counsellors

played an important role in assisting students learn about specific institutions.

In sum, when students must make the decision concerning which college to

attend, they tend to consult family, friends, peers, teachers, counsellors, and college

recruiters. All these individuals will have a certain degree of influence on the

students’ decision (Stefanie, 2006).

Family and Parental Influence

The influence of the family on college attainment for students and the way the

family imparts values differs from what the research indicates about the influence of

the family towards college attainment for all students (Freeman, 1997; Wilson &

Allen, 1987).

Descriptive and univariate analyses by Hossler et al. (1999) revealed that

students in the ninth grade who talked the most with their parents (rather than with

peer, teachers, or counsellors) about their postsecondary plans were more likely to be

planning to attend college and were also more likely to be certain of their plans. Many

studies have shown that parental encouragement is highly influential on a student’s

college choice. The research of Carpenter and Fleishman (1987) revealed that as the

level of parental encouragement increased, student achievement also increased.

30

According to Cabera and La Nasa (2000), parental encouragement has two

dimensions; motivational and proactive. In the motivational stage, parents maintain

high educational expectations for their children. During the proactive stage, parents

become involved in school matters, discuss college plans with their children and save

for college (Stage & Hossler, 1989; Flint, 1992, 1993; Hossler & Vesper, 1993;

Miller, 1997; Hossler et al, 1999; Perna, 2000).

In other words, to know students’ and their parents’ expectations could be one

of the effective ways that colleges have to take to face the highly competitive new

environment (Thomas et al., 1996; Walther, 2000; St. John et al., 2005; Schweitzer,

2006).

Friends’ Influence

According to Hayden (2000), opinions of friends and former students weigh

heavily on the minds of college applicants when deciding between colleges. These

studies and others expound upon the knowledge that the more a high school student

interacts with other students with college plans, the more likely they are to consider

going to college.

Maringe (2006), Hemsley-Brown and Oplatka (2006) found that

approximately 27% of the students turned to their friends and neighbours for their

HEI choice. This is because formal sources of interpersonal information such as

agents, experts, university staff and counsellors are less easily accessed than informal

sources such as friends, family, neighbours and relatives. However, formal sources

31

may be more believable if the product is perceived to be highly technical and high

involvement (Coccari et al. 1995).

Peers’ Influence

Hossler and Stage (1987) showed a correlation between non-college bound

students and their non college bound peers. These researchers stated that students with

peers with no college plans influence the predisposition phase of students; college

choice. Their research also found that students who were not planning to attend a HEI

were more likely to consult their peers. While parental encouragement is still

considered the greatest influence on college attainment, the effect of student’s peers

does add an additional dynamic to the overall college choice process for high school

students.

Several researchers (Coleman, 1966; Tillery, 1973; Russell, 1980; Falsey &

Haynes, 1984) examined the relationships between student interaction with other

college bound students and their college participation.

Teachers and Counsellors’ Influence

Leslie et al. (1977) reported research data that shows that students are most

likely to rely on information about college from their high school counsellor. This

study concluded that upper income students cite parents, students, catalogues, college

representatives, and private guidance counsellors as sources for information on their

college search.

32

Researchers have studied the influence of high school personnel on the college

choice of minority students (Lewis & Morrison, 1975; Hossler & Stage, 1997).

Research indicates that minority students are more likely to consult with counsellors

about their college choice.

According to the literature discussed in this section, a variety of attributes

have been identified as influencing factors in the decision-making process of students’

intention to study at a HEI. Therefore, a multi-attribute model is proposed to provide

tertiary institutions with a set of important attributes that students use in their decision

making for their further study. These important attributes are summarized in Table

2.1.

33

Table 2.1: Summary of important attributes that affect students’ intention to study at a HEI

Reference Important Attributes 1 Baird (1967) Good faculty

High academic standards Special programmes

2. Bowers and Pugh (1972) Good faculty

High standards 3. Chapman (1979) Quality of the institution

Cost of education 4. Murphy (1981)

Academic reputation Cost of education

5. Maguire and Lay (1981) Financial aid

Peer influence Special programmes Size of the institution Location Athletic facilities Social activities

6. Krampf and Heinlein (1981) Attractiveness of the campus

Recommendation from family Closeness to home Good programme in their major Friendliness of the campus atmosphere Informative campus visits Informative university catalogue

7. Hooley and Lynch (1981) Course suitability

Academic reputation University location Distance from home Advice from parents and teachers Type of university (morden/old)

8. Chapman (1981) Significant person

Fixed college characteristics College efforts to communicate with

students 9. Discenza et al. (1985), Hossler

(1985) Academic reputation Peer influence, financial assistance, and

location 10. Litten (1980), Seneca

and Taussig (1987) and Tierney (1983)

Good programmes Social life

34

Reference Important Attributes 11. Houston (1979), Krone et

al. (1983), Webb (1993) Flexibility and length of the programme Reputation and prestige Cost of education

12. Qureshi (1995) University reputation

Wide selection of courses Total cost of attendance Availability of financial aid Reputation of the programme

13. Mazzrol et al. (1996) Recognition of their qualification by future

employers Quality reputation Willingness to recognize previous qualification Staff’s quality, reputation and expertise

14. Lin (1997) Quality of education offered

Degree opportunities Reputation of institution Internship opportunities Faculty qualifications Academic standards Availability of modern facilities Curriculum Emphasis Student life Student bodies

15.

Turner (1998) Future job prospects Recognition of qualification by employers Availability of modern facilities Teaching standard International recognition of programme

16. Joseph and Joseph (1998,

2000) Value of education Degree (content and structure) Cost of education Physical aspect and facilities General (Information and influence of family

& friends) 17. Soutar and Turner (2002) Course suitability

Academia reputation Job prospects Teaching quality Campus atmosphere

35

Reference Important Attributes 18. Pimpa (2003) Family influences (finance, information,

expectation, competition, persuasion)

19. Price et al. (2003) Course suitability Availability of computers Quality of library facilities Good teaching reputation Availability of “quiet” areas

20. Chen and Zimitat (2006) Environmental

Cultural and attitudinal influences Social class Family influence

2.6 Review of Multiple Attribute Researches

Several relevant analyses were demonstrated by different researchers to study the

factors that influence students’ intention to study at a HEI. As discussed in Section

2.5, studies indicate that students consider several factors when it comes to choosing a

HEI to attend. In this section, findings of those researches described multiple

attributes that influence students’ intention to study at a HEI, instead of reliance on a

single attribute.

Krampf and Heinlein (1981) undertook one of the earliest studies into the

marketing of universities, interviewing prospective students for a large mid-western

university in the USA. Their objective was to determine the needs of the prospective

student market, examine the university's image, and develop ways of identifying

potential students who had a high probability of matriculating and were eligible for

entry. Their sample was collected from the American College Testing program, which

provides more than 100 pieces of information for each student who completes their

profile. Using factor analysis, they found that prospective students who had a positive

attitude towards the university rated highly the attractiveness of the campus,

36

informative campus visits, recommendation of family, good programmes in their

major, informative university catalogue, closeness to home and the friendliness of the

campus atmosphere, suggesting that these factors might influence preferences.

Hooley and Lynch (1981) examined the choice processes of prospective

students of UK universities via a conjoint analysis. Qualitative research was used to

determine the attributes used in the decision process, followed by face-to-face data

collection using stimulus cards to obtain preferences for a set of experimentally

chosen university profiles. The six attributes that Hooley and Lynch (1981) identified

were course suitability, university location, academic reputation, distance from home,

type of university (modern/old), and advice from parents and teachers. The conjoint

analysis suggested that course suitability was the most important attribute in

determining university choice. According to Lynch (1981) prospective students

appeared to be prepared to accept that the conjoint approach was helpful and that a

larger study would permit more reliable conclusions to be drawn.

Oosterbeek et al. (1992) examined university choice and graduates' earnings in

the Netherlands. Their objectives were to determine whether different universities

were associated with different earnings prospects and whether the decision to attend a

particular university was influenced by these prospects. They found that although

there were significant differences, earnings prospects were not a particularly

important factor in the choice of a specific university.

Mazzarol et al. (1996) examined the factors that influenced international

students' choice of study destination using a sample of students studying in Australia.

Students were asked to rate the importance of 17 factors to their decision to study at a

37

particular institution. They found that the most important selection factor was the

recognition of their qualifications by future employers. This was followed by the

institution's reputation for quality, its willingness to recognize previous qualifications

and the staff's reputation for quality and expertise.

Lin (1997) investigated the reasons for students' intention to study at an

educational institution in the Netherlands. Self-completion questionnaires were

randomly distributed to students in the lobbies of seven universities. A combination of

descriptive and factor analysis was used to identify the main reasons for their choice

of institution. The most significant reasons for a student's choice of institution were

the quality of education offered, career opportunities, the school's reputation,

opportunity for traineeships, faculty qualifications, academic standards, whether

modern facilities were available, curriculum emphasis, student life and whether there

was an international student body.

Turner (1998) undertook a study of business undergraduates to determine their

reasons for choosing to enrol at a particular university. Students rated the most

important factors as future job prospects, obtaining qualifications that were valued by

employers, being able to use modern facilities, the standard of teaching and the

international recognition of the university's programmes.

Joseph and Joseph (1998, 2000) found that students from different

geographical areas revealed different preferences of attributes towards a HEI.

Moreover, they identified that male and female students differ in the selection criteria

they consider important when choosing a HEI. Some relevant multiple-attribute

analyses are summarized in Table 2.2.

38

Table 2.2: The literature concerning multiple-attributes employed in previous studies

Reference Analysis Applied Kind of Study Top Five Factors Identified/Main Finding

1. Chapman (1981) Model of Student College Choice (combined model)

QT/QL 1. Significant persons 2. Fixed college characteristics 3. College efforts to communicate with student

2. Krampf and Heinlein (1981)

Multiple discriminant analysis QT Finding: Identifies the steps a prospective user would follow 1. Attractiveness of the campus 2. Recommendation from family 3. Closeness to home 4. Good programme in their major 5. Friendliness of the campus atmosphere

3. Hooley and Lynch (1981)

MONANOVA Conjoint analysis

QT/QL Finding: Need of segmentation of prospective students 1. Course suitability 2. Academic reputation 3. University location 4. Distance from home 5. Advice from parents and teachers

4. Qureshi (1995) Correlation analysis ANOVA Model of Consumer Behaviour

QT 1. University reputation 2. Wide selection of courses 3. Total cost of attendance 4. Availability of financial aid 5. Reputation of the Programme

Notes : QT = Quantitative, QL = Qualitative

39

Reference Analysis Applied Kind of Study Top Five Factors Identified/ Main Finding

5. Lin (1997) Descriptive analysis Factorial analysis

QT 1. Quality of education offered 2. Degree opportunities 3. Reputation of institution 4. Internship opportunities 5. Faculty qualifications

6. Mazzarol (1998) Factor analysis Logistic regression model

QT 1. Image and resources 2. Coalition and forward integration

7. Joseph and Joseph (1998, 2000)

Multi-attribute Model Descriptive analysis Ranking-Important Rotated factor score analysis

QT/QL New Zealand Students: 1. Value of education 2. Degree (content and

structure) 3. Cost of education 4. Physical aspect and

facilities 5. General (Information and

influence of family & friends)

Indonesian Students: 1. Course and career information 2. Physical aspect and facilities 3. Cost of education 4. Degree (content and structure) 5. Value of education

8. Ivy (2001) Correspondence analysis QT Old UK Universities: 1. Top quality teaching 2. Research output 3. The range of courses offered 4. Staff reputation

South African Technikon: 1. Lower fees 2. Including bursaries 3. Physical facilities 4. Part-time tuition

Notes : QT = Quantitative, QL = Qualitative

40

Reference Analysis Applied Kind of Study Top Five Factors Identified/ Main Finding

9. Soutar and Turner (2002)

Combined analysis/Conjoint analysis Cluster analysis

QT 1. Course suitability 2. Academic reputation 3. Job prospects 4. Teaching quality 5. Campus atmosphere

10. Binsardi and Ekwulugo (2003)

Ranking-independence analysis of Chi-square statistics

QT/QL Country Aspects: 1. Education standard/recog.

qualify - worldwide 2. Ease of university admissions 3. Ease of immigration

procedures 4. Ease of finding employment 5. Cost of living, accommodation,

safety and culture

Institution Aspects: 1. Lower tuition fee 2. Providing more

scholarship 3. Providing better quality

care and services 4. Supplying more facilities 5. Alumni networks

international students

11. Price et al. (2003) Descriptive analysis QT/QL 1. Course suitability 2. Availability of computers 3. Quality of library facilities 4. Good teaching reputation 5. Availability of “quiet” areas

Notes : QT = Quantitative, QL = Qualitative

41

2.7 Gender Effect on HEI Selection

Literature cited the notion that in general, males and females differ in their

psychological orientation along the dimensions of agency and communion (Bakan,

1966; Meyers-Levy, 1988). Meyers-Levy (1988) determined that males are

characterized as being relatively self-focused and are guided by agency goals

encompassing self-assertion and achievement-oriented concerns; whereas, females are

more sensitive to the needs of both self and others and are guided by communal

concerns including interpersonal affiliation, a desire to be at one with others, and

harmonizing relations between themselves and disparate parties. Hence, this theory

offers a partial explanation for why there are gender differences in processing

strategies (Laroche et al, 2000).

Meyers-Levy and Mahjeswaran (1991) and Meyers-Levy and Sternthal (1991)

assess differences in processing strategies based on a selectivity model, which

indicates that females attempt to engage in effortful, comprehensive, itemized analysis

of all available information giving equal weight to information relevant to self and

others. Whereas, males often do not engage in the comprehensive processing of

information, but rather they are selective information processors processing

heuristically and, therefore, missing subtle cues. In addition, males tend to rely on a

single cue or cues that are highly available and particularly salient in the focal

context.

These suggested differences between genders should be of interest for HEIs

across the nation as such knowledge will enable colleges to better understand their

targeted customers, as well as allowing HEIs to assess how and to what extent

42

changes occurring in the gender roles are likely to impact the kinds of appeals that

will be effective with students, both male and female (Mansfield and Warwick, 2005).

This view is supported by previous research findings. A pilot study by Schab

(1974) reported that the women in his sample frequently chose nonprofessional

reasons as explanations for why they were attending college. He found that women

viewed the motives for attending college of other women as: finding a suitable

husband, pleasing their parents, having fun, being able to rear their children better,

and pledging a particular sorority. Schab’s findings suggested that it was unclear if

women were attending college in order to gain knowledge that would prepare them

for the workforce.

Hayes et al. (1995) demonstrated a research on gender differences by using a

different targeted population, different-determinant attributes and by exploring other

issues in the decision-making process of choosing a HEI. Specifically, the research

explored the impact of gender on two integral components of the college decision-

making process – the importance of determinant attributes of a university and the

importance of various information sources when choosing a university.

Shank and Fred (1998) performed a study regarding gender differences in the

university selection process. Results indicated that male and female students differ in

terms of the importance placed on various attributes of a university.

Jacobs (1999) described that the significant gender differences found among

high school seniors may be more important than ever as women now constitute the

43

majority of associate and other two year degree recipients, the majority of bachelor's

degree recipients, about half the master's and professional degree recipients, and

nearly 40% of doctoral degree recipients.

A more recent study reported that females attend college primarily to improve

their chances of success in the workplace (Green & Hill, 2003). This led us to probe if

there are different influential factors for choice of colleges between males and

females. In conclusion, there is no doubt that male and females differ in their decision

making for HEI attendance.

2.8 Academic Background Effect on HEI Selection

The Chapman (1981), Freeman (1999) and Cabera and La Nasa’s (2000) models all

illustrate aspects of student characteristics as an influencing factor to college

selection. Each of these three models examine the influence of academic status such

as the highest academic qualification, courses attended during high school, high

school achievement or academic ability and educational aspiration as characteristics

of students, which researchers have concluded influence how students conclude their

college choice.

Additionally, Sohail and Saeed (2003) claimed that in the Malaysian context,

the courses that students attended at pre-university or high school is positively

associated with a predisposition to attend a HEI in the future. Furthermore, Elizabeth

Ng (2003) observed that Malaysian students who studied in different programmes at

pre-university level have a distinct perception towards their HEI preference. In sum,

44

students coming from different academic backgrounds may have a distinctive

perceived importance on the attributes of a HEI.

2.9 Conclusion of the Chapter

This chapter discussed the relevant literature comprehensively. It is apparent that

there are several important attributes that influence students’ intention to study at a

HEI. These attributes were grouped in categories for the purpose of this study. As

discussed in earlier sections, the groups of attributes are cost of education, degree

(content and structure), physical aspects, facilities and resources, value of education,

institutional information, and People (Family, Friends, Peers and Teachers).

Also, the literature revealed that there are gender and academic background

differences in the importance students’ place on these attributes. The relationships and

the differences between these attributes will be further discussed in the next chapter.

CHAPTER 3

Conceptual Model

3.1 Introduction

3.2 Conceptual Model

3.3 Definition of Variables

3.4 Hypotheses Development

3.4.1 Cost of Education

3.4.2 Degree (Content and Structure)

3.4.3 Physical Aspects, Facilities and Resources

3.4.4. Value of Education

3.4.5 Institutional Information

3.4.6 Influences from People (Family, friends, peers and

Teachers)

3.4.7 Gender Differences on Important Attributes of HEI

3.4.8 Academic Background Differences on Important

Attributes of HEI

3.5 Conclusion of the Chapter

Chapter 1 Introduction

Chapter 2 Literature Review

Chapter 3 Conceptual Model

Chapter 4 Research Methodology

Chapter 5 Data Analysis and

Findings

Chapter 6 Discussion and

Conclusion

3.1 Introduction 3.2 Conceptual Model 3.3 Definition of Variables 3.4 Hypotheses Development 3.5 Conclusion of the Chapter

45

CHAPTER 3 CONCEPTUAL MODEL

3.1 Introduction

This chapter presents the study using the theoretical approach, the proposed

conceptual model, variables and the research hypotheses. The research hypotheses

include the relationship between these important influencing factors and students’

intention to study at a HEI. In addition, research hypotheses also cover the difference

concerning important attributes among students’ gender and academic background.

The development of the conceptual model is extensively discussed, and the variables

are defined in this chapter.

3.2 Conceptual Model

The theoretical model is adapted from a previous study by Cubillo et al. (2006).

Previous study proposes a theoretical model that integrates the different groups of

factors that influence the decision-making process of international students. The

theoretical model comprises the purchase intention, as a dependent and not observable

variable, and four factors with a total of 19 items identified from the existing

literature. The factors identified are personal reasons, country image, institution

image, and programme evaluation. The theoretical model is presented in Figure 3.1.

Modifications to the developed theoretical model are proposed in order to

accommodate the purpose of this study. The developed theoretical model has been

modified by substituting the five existing independent variables (IVs) with six IVs

that were adopted from Joseph and Joseph (1998, 2000). The six substituted IVs are

46

cost of education, degree (content and structure), physical aspects, facilities and

resources, value of education, institutional information, and influences from people

(family, friends, peers, and teachers). The theoretical model is modified in such a way

to study the important attributes that influence students’ intention to study at a HEI,

which is in line with the objectives of this study.

Figure 3.1: A model of international students’ preference by Cubillo et al. (2006)

In addition, a further modification of the items within the IVs adopted from

Joseph and Joseph (1998, 2000) is made to address the important attributes that

influence students’ intention to study. The dependent variable (DV) proposed in this

study is the students’ intention to study at a HEI. This variable has the same

magnitude as the DV (purchase intention) in the adapted model. According to the

favourable behavioural intention studies demonstrated by Zeithaml et al. (1996), it

was found that certain behaviours signal that customers are forging bonds with a

company. When customers praise the firm, express a preference for the company over

Purchase Intention

Personal Reasons (3 Items)

Country Image Effect (3 Items)

Institution Image (5 Items)

Programme Evaluation (4 Items)

City Image (4 Items)

47

others, increase the volume of their purchase, or agreeably pay a price premium, they

are indicating behaviourally that they are bonding with the company. The

phenomenon is similar to the HEI industry, in this case students act as customers. If

students intend to study at a HEI, the students reveal a favourable behavioural

intention towards the HEI. In turn, students may say positive things about the HEI,

recommend the HEI to others, remain loyal to the HEI, spend more time with the HEI,

and pay a premium rate for the HEI (Parasuraman et al., 1996). The proposed

conceptual model of this study is shown in Figure 3.2

Figure 3.2: The proposed conceptual model in this study, adapted from Zeithaml et

al. (1996), Joseph and Joseph (1998, 2000), and Cubillo et al. (2006).

Intention to Study at a Higher Educational

Institution

Cost of Education

Degree (Content and Structure)

Physical Aspects, Facilities and Resources

Value of Education

Institutional Information

Family, Friends and Peers

48

The model presented in this study aims to explain the factors influencing the

study intention of Malaysian students. The intention to study is used as a predictor for

the preferential choices of students, and is defined as the intention of the student to

study at a particular HEI (Peng et al., 2000; Srikatanyoo and Gnoth, 2002; Cubillo et

al., 2006).

3.3 Definition of Variables

Items of IVs are adopted from the previous studies by Joseph and Joseph (1998,

2000). The items of DV are adopted from Zeithaml et al. (1996). These items are

reorganized in such a way as to be applicable in the Malaysian context. The definition

and items for each variable is summarized in Table 3.1.

Table 3.1: The definition of each variable in the study

Independent Variable Cost of education (IV1) Definition: Students’ financial consumption during study (Foskett et al, 2006) Five Measurable items - Reasonable cost - Availability of financial aid - Availability of scholarship - Flexible payment of fee - Accommodation at reasonable cost

1.

Sample item Provides education at a reasonable cost

49

Independent Variable Degree (Content and Structure) (IV2) Definition: The availability and suitability of the offered courses to students

(Hooley and Lynch, 1981) Five Measurable items - Reasonable entry requirements - Wide range of courses - Flexibility in selecting courses/subjects - Specialized programmes - Reasonable completion periods of study

2.

Sample item Have reasonable entry requirements for its programme Physical Aspects, Facilities and Resources (IV3) Definition: Institutes’ structures and properties (Price et al., 2003) Eight Measurable items - Ideal Location - Environment conducive to learning - Great recreation and other facilities - Expected social life on campus - Availability of necessary resources (include facilities) - Cleanliness - Safety - Quality faculty members

3.

Sample item Be situated in an ideal location

4. Value of Education (IV4) Definition: The preserved importance and principles of quality education (Kotler

and Fox, 1995)

Five Measurable items - Well known reputation - Well known academic values - Recognition from other academic institutions - Recognition from professional bodies - Recognition from respected industries

Sample item Well known reputation

50

Independent Variable Institutional Information (IV5) Definition: Information made available by institutions to students (Cleopatra,

2004) Five Measurable items - Application process - information availability - Career opportunities - Area of study - Post-graduate studies

5.

Sample item Provide students with information regarding application processes People (Family, Friends, Peer and Teachers) (IV6) Definition: Influences of family members, friends and peers that affect students’

intention to study (Sheppard et al., 1992) Eight Measurable items - Rely on family members’ opinion - Family views are important - Rely on friends’ advice - Friends’ perceptions are important - Rely on peers’ idea - Peers’ suggestions are vital

- Rely on teachers’ view - Teachers’ recommendations are vital

6.

Sample item I usually rely on my family member’s opinion

Dependent Variable Intention to Study at a Higher Educational Institution (DV) Definition: Students’ intention to further their study at a higher educational

institution (Mazzarol, 2000) Six Measurable items - Likelihood to further study - Strong interest to pursue study - Recommend the chosen HEI - Say favourable things about the chosen HEI - Willing to spend - Willing to pay at high rate

1.

Sample item The likelihood to further my study at a HEI is high

51

3.4 Hypotheses Development

3.4.1 Cost of Education

In a previous study, James et al. (1999) stated that overall costs incurred have not

usually been a strong influence in the applicants’ decision and choice of university.

While confirming the above, research done in England (Fokskett et al., 2006)

suggests factors influencing students’ intention to study at a HEI could be turned

upside down now that financial considerations are of greater importance to students.

Moreover, the recently announced introduction of student fees in HEIs may result in

greater consumerist behaviour by applicants as the issue of “value for money” may

become a major factor affecting students’ decision making.

Thus, this study hypothesises that the cost of education is a significant factor

that influences students’ intention to study at a HEI in the Malaysian context.

H1: The cost of education is a significant factor that influences students’ intention to

study at a HEI

3.4.2 Degree (Content and Structure)

Studies (Mazzarol, T. 1997, 1998, 1999) have found that the majority of students

when making decisions for their further study only have limited knowledge about the

programme and its content. Thus, it may be argued that the ability of a HEI to offer a

wide range or specialised courses for its students is not the main factor that attracts

student’s intention to study at the HEI. Nevertheless, some other researchers

expressed contrasting opinions.

52

Hooley and Lynch (1981) observed that the suitability of the programme is the

most important factor, as students will accept any level of the other factors. In this

sense, prospective students will compare programmes offered with those being

promoted by competing institutions in order to check their suitability (Krampf and

Heinlein, 1981). Consequently, this study hypothesises that the content and structure

of degree is a significant factor that influences students’ intention to study at a HEI in

the Malaysian context.

H2: The content and structure of the degree is a significant factor that influences

students’ intention to study at a HEI

3.4.3 Physical Aspects, Facilities and Resources

Some researchers cited that the physical aspects of a HEI, including its location and

good social life on campus, are not usually the determinants in students’ intention to

study at a HEI (Robert, 1998; Hemsley-Brown, 1999).

However, Price et al. (2003) found that when provided, high standard facilities

are considered as a relevant factor that influence the students’ selection of institution

for the pursuit of their studies. Hence, this study hypothesises that the physical

aspects, facilities and resources of an institution form a significant factor that

influences students’ intention to study at a HEI in the Malaysian context.

H3: The physical aspects, facilities and resources of an institution are a significant

factor that influences students’ intention to study at a HEI

53

3.4.4 Value of Education

Concerning the influence on student’s intention to study at a particular HEI in

comparison with other factors, previous studies (Foskett, 1999; Smith et al, 2002)

indicate that relatively the academic value of education is not an important factor.

In contrast, some researchers found that the value of education does play a role

in the students’ decision making process concerning further study. Joseph and Joseph

(1998, 2000) found that the value of education is the most important factor to be

considered by New Zealand students in their planning for further study, however, the

impact level varies between countries. Accordingly, this study hypothesises that the

value of education is a significant factor that influences students’ intention to study at

a HEI in the Malaysian context.

H4: The value of education is a significant factor that influences students’ intention

to study at a HEI

3.4.5 Institutional Information

Studies (Turner, 1998) have found that the institutional information does not have a

major affect on students’ intention to study at a HEI. Studies also indicate that in the

decision making process for further study, most students consider other factors as

being more important and that institutional information only acts as a guide for them.

However, there are arguments that institutional information is an important

factor that influences students’ intention to study at a HEI due to its ability to convey

a significant message that affects the decision making process. In addition, some

researchers argued that the comprehensive information provided by a HEI is the

primary factor that determines students’ intention to study at the HEI (Cleopatra,

54

2004). Therefore, this study hypothesises that the institutional information is a

significant factor that influences students’ intention to study at a HEI in the Malaysian

context.

H5: The institutional information is a significant factor that influences students’

intention to study at a HEI

3.4.6 Influences from People (Family, Friends, Peers and Teachers)

Results from previous studies (McMahon, 1992, Kemp, 1995), showed that many HEI

marketers were of the opinion that students who intend to continue their studies at a

higher level were often those that were considered mature, independent and in

possession of a critical thinking mentality. Hence, they concluded that the influence of

students’ family, friends and peers was not the main factor affecting their intention to

study at a HEI.

Nevertheless, recently many academic researchers have found that family

members and friends act as significant people that encourage students to study at a

HEI (Krampf and Heinlein, 1981; Turner, 1998; Bourke, 2000). Moreover, this

situation is more obviously revealed in the Asian context based on research results

(Pimpa, 2003; Chen and Zimitat, 2006). As a result, this study hypothesises that the

significant people (family, friends, peers and teachers) are a significant factor that

influence students’ intention to study at a HEI in the Malaysian context.

H6: The significant people (family, friends, peers and teachers) is a significant factor

that influences students’ intention to study at a HEI

55

3.4.7 Gender Differences on Important Attributes of HEI

Numerous studies have addressed the differences between males and females with

regard to their psychological orientation and behaviour. From a consumer behaviour

perspective (in this study, students as customers), there have been several studies

directed towards gender differences. Studies have addressed gender differences in

information processing strategies (Meyers-Levy and Maheswran, 1991), roles and

attitudes (Fischer and Arnold, 1994), cueing and judgment-related activities (Meyers-

Levy and Sternthal, 1991), and right-brain/left- brain activity (Meyers-Levy, 1994) to

name a few.

Previous studies have also found judgment-related differences between males

and females when evaluating promotional materials, and their attentiveness to

different forms of advertising appeals (Holbrook, 1986; Meyers-Levy, 1994). This

finding may draw the attention from HEI marketers and is significant in advertising

and promotion strategies.

Given that research has also found gender differences in shopping behaviour

(Roberts and Wortzel, 1984; .Zeithaml, 1985) and in the characteristics males and

females consider when evaluating products (Fischer and Arnold, 1994; Meyers-Levy

and Sternthal, 1991), it is likely that gender differences are extended to the evaluative

criteria in the selection of a college. As a result, this study hypothesises that there are

significant differences between students’ gender concerning the importance placed on

the factors that influence students’ intention to study at a higher educational

institution.

H7: Male and female students differ in the importance placed on the factors that

influence students’ intention to study at a higher educational institution.

56

3.4.8 Academic Background Differences on Important Attributes of HEI

Sohail and Saeed (2003) proposed that the different academic background of students

leads to different preferences towards a HEI. Other researchers found that students,

who come from a distinct academic background, especially those who studied

different courses at pre-university level, revealed different perceptions of which HEI

to attend (Hassan and Shariff, 2006).

Nevertheless, a few studies were found that addressed the differences in

students’ academic background with regards to the HEI selection process in the

Malaysian context. Consequently, this study hypothesises that there is a significant

difference between students’ academic background and the importance placed on the

factors that influence students’ intention to study at a higher educational institution.

H8: Students with different academic background will differ in the importance placed

on the factors that influence students’ intention to study at a higher educational

institution.

A comprehensive conceptual model and the proposed hypotheses are presented

in Figure 3.3.

57

Independent Variables, IVs Dependent Variable, DV

Figure 3.3: The conceptual model and proposed hypotheses in the study

As a summary, in total there are eight proposed hypotheses in this study:

H1: The cost of education is a significant factor that influences students’ intention to

study at a HEI

H2: The content and structure of the degree is a significant factor that influences

students’ intention to study at a HEI

H3: The physical aspects, facilities and resources of an institution are a significant

factor that influences students’ intention to study at a HEI

Cost of Education (5 Items, Interval)

Degree (Content and Structure) (5 Items, Interval)

Physical Aspects, Facilities and Resources

(8 Items, Interval)

Value of Education (5 Items, Interval)

Institutional Information (5 Items, Interval)

People (Family, Friends, Peers and Teacher)

(8 Items, Interval)

H1

H2

H3

H4

H5

H6

Students Intention to study at a Higher Educational Institution

(6 Items, Interval)

58

H4: The value of education is a significant factor that influences students’ intention

to study at a HEI

H5: The institutional information is a significant factor that influences students’

intention to study at a HEI

H6: The significant people (family, friends, peers and teachers) is a significant factor

that influences students’ intention to study at a HEI

H7: Male and female students will differ in the importance placed on the factors that

influence students’ intention to study at a higher educational institution.

H8: Students with different academic background will differ in the importance

placed on the factors that influence students’ intention to study at a higher

educational institution.

3.5 Conclusion of the Chapter

This chapter discussed the development of the proposed conceptual model. This

model combines a few previous studies as a platform, allowing the present study to

investigate the relationships between variables, and the difference in students’ gender,

and academic background concerning their intention to study at a HEI. Each proposed

variable is comprehensively defined in this chapter.

A total of eight research hypotheses have been developed to address the

research objectives and research question. These hypotheses will act as the guide to

the sequential analysis, which will be discussed in Chapter 5. The next chapter

discusses the detail of the research methodology employed in this study.

CHAPTER 4

Research Methodology

4.1 Introduction

4.2

4.3 Selection of Sample

4.4 Sampling

4.5 Instrument Design

4.6 Data Collection

4.7 Research Approaches

4.7.1 Determination of Sample Normality

4.7.2 Descriptive Analyses

4.7.3 Validity Test

4.7.4 Reliability Test

4.7.5 Relationship Approach

4.7.6 Differences Approach

4.8 Assumptions of the Study

4.9 Conclusion of the Chapter

Chapter 1 Introduction

Chapter 2 Literature Review

Chapter 3 Conceptual Model

Chapter 4 Research Methodology

Chapter 5 Data Analysis and

Findings

Chapter 6 Discussion and

Conclusion

4.1 Introduction 4.2 Research Design 4.3 Selection of Sample 4.4 Sampling 4.5 Instrument Design 4.6 Data Collection 4.7 Research Approaches 4.8 Assumptions of the Study 4.9 Conclusion of the Chapter

59

CHAPTER 4 RESEARCH METHODOLOGY

4.1 Introduction

This chapter reveals the research methodology employed in the present study. The

chapter begins with a discussion on the sample selection and sampling, followed by

instrument design and data collection. A complete methodology of the performed

analyses is discussed in the later section of this chapter.

4.2 Research Design

The research design is the blueprint for fulfilling objectives and answering questions.

In this study, the qualitative approach was employed as the theories are well

developed and lead to a formal conceptual model. As a result, hypotheses can be

developed and tested. The instrument was adapted from previous studies (Zeithaml et

al., 1996; Joseph and Joseph, 1998 & 2000). The instrument was a self-administered

questionnaire that was distributed to the respondents in the form of survey, and the

data collected was primary data for the analysis.

4.3 Selection of Sample

The targeted sample of this study was students who were currently attending pre-

university level programmes, including Form Six (high school), GCE A-Level, local

matriculation, overseas Pre-U courses, and other foundation courses. Recent school

leavers, for instance, those students who graduated from their secondary school within

the previous two years were eligible for participation in this study. However, no

school leavers participated in the study; all respondents were currently attending pre-

university level programmes.

60

The targeted sample was defined as such, as these groups of people have the

highest possibility of continuing their study at a HEI. In other words, their intention to

continue their study at a HEI was assumed. Consequently, they are of interest to HEI

marketers for identifying what factors influence the students’ intention to study at a

HEI. Moreover, knowing the reasons why students choose a university and course of

study is central to developing institutional positioning in an increasingly competitive

HE environment.

4.4 Sampling

As mentioned in Chapter 1, most of the PHEIs that conduct pre-university courses

are concentrated around major urban areas in the Klang Valley. Moreover, the number

of public schools that offer Form Six (STPM) in this area is higher than other states.

As a result, a sample from this segment may adequately represent the actual

population. Thus, this study focuses on Malaysian students who are currently

attending courses at the pre-university level around the Klang Valley.

Sampling was carried out in selected PHEIs, matriculation centres and tuition

centres. The samples were collected using stratified convenience sampling. Using this

method, the selection of sample for this research was based on the appropriateness of

the research objectives; specifically, the respondents’ academic background (as

respondents’ highest qualification in questionnaire) was divided into three distinct

categories with a minimum of 150 responses each; as presented in Table 4.1.

Therefore, respondents were asked to identify their study status, and then only

qualified respondents were considered for participation in the sampling process.

61

Table 4.1: Purposive sampling and targeted response

Academic Background Targeted Response 1. Form Six/STPM 150 2. GCE A-level 150 3. L.O.U. 150 Total 450 * L.O.U. = Local matriculation, overseas Pre-U, university foundation programme

4.5 Instrument of Measurement

The instrument used in this study was designed based on prior published researches

regarding the important factors affecting students’ selection of a HEI. A multiple

attribute model was developed for use in this study by adapting those employed in

previous studies (Zeithaml et al., 1996; Joseph and Joseph, 1998 & 2000; Cubillo et

al., 2006).

The instrument was a structured self-administered questionnaire that was

distributed to the respondents in the form of survey and then collected back for use as

the primary data. Basically, the questionnaire contained three sections:

Section A: Attributes that affect university or college choice

Section B: Ranking order of important attributes

Section C: Respondents demographic information

In Section A, items were designed to measure and compare the importance of

factors that influence respondents’ intention to study at a HEI. The questionnaire

comprises 42 items and seven variables; six IVs and a DV. The measurable items of

IVs and DV were adapted from previous researches done by Joseph and Joseph (1998

& 2000) and Zeithaml et al. (1996), respectively. Responses to both the IVs and DV

were measured based on a five-point Likert scale, in increasing order, ranging from

“strongly disagree”, “disagree”, “not sure”, “agree”, to “strongly agree. In order to

make the survey easy and convenient for the respondents, the five scales were

62

displayed in numerical form in the questionnaire, where one represented “strongly

disagree”, and five represented “strongly agree”.

In Section B, a table was provided for respondents to place the ranking order

in the blank column, regarding their perceived importance of factors influencing their

intention to study at a HEI. The ranking order of important factors ranged from one to

six in decreasing order of importance. For example, one represented the most

important factor, whereas six represented the least important factor. An example was

give next to the table to provide assistance in answering the section correctly and to

avoid any confusion.

Section C, consisted of a series of questions addressing the respondents’

demographic information. These questions were used to identify the respondents’

gender, age group, ethnic group, religion, highest academic qualification, family size

and gross monthly income. Based on the obtained demographic data, the respondents’

characteristics could be identified. It was significant in this study as stratified

sampling was applied and, therefore, responses from the subgroups must be in line

with the proposed quantity. In this case, respondents’ academic background was the

controllable stratum.

4.6 Data Collection

Self-administered questionnaires were distributed in the form of a survey and

completed by the respondents. The respondents were informed that participation was

voluntary. The data collection was completed with assistance from lecturers from

HEIs, and teachers from tuition centres. The results of the sampling are presented in

Chapter 5.

63

4.7 Research Approaches

Data was coded using Statistical Package for Social Studies (SPSS), version 15.0.

Data was screened and cleaned in order to identify any significant outlier or missing

value.

4.7.1 Determination of Sample Normality

In order to perform the parametric analyses on the samples, all collected scale type

data from the survey was subject to exploration for the normality tests before

subsequent analyses. The objective of sample normality tests is to ensure the sample

is normally distributed and randomly selected. It is important that the normality of the

sample is confirmed before subjecting it to inferential and differential analyses, as it

proves the capability and appropriateness of the sample in representing the actual

population. Thus, the findings from consequent analyses in this study can be

generalized to the population with confidence.

Several normality tests were carried out on the data by employing graphical

and statistical analyses on the sample as shown in the following table:

Table 4.2: Normality tests employed in this research

Method Analysis

1. Histogram Graphical

2. Stem-and-leaf Plots Graphical

3. Boxplot Graphical

4. Descriptive Statistics Statistical

64

4.7.2 Descriptive Analyses

Descriptive analyses were performed on two distinctive sections of the collected data,

namely, Section A and Section B. The analyses were:

Section A: Mean and standard deviation for items in each variable; and

computed mean and standard deviation for the variables.

Section B: Rank ordering score for the influencing factors.

4.7.3 Validity Test

The validity test of the instrument in this study was performed by factor analysis.

Generally, factor analysis is carried out to condense a large set of scale items down to

a smaller, more manageable number of factors. It can be done by summarizing the

underlying patterns of correlation and looking for groups of closely related items.

In this study, there were 36 items allocated in seven variables, including six

IVs and a DV. The objective of the validity test in this study was to identify whether

the proposed items were valid for measuring the underlying concept. In this case, the

concept referred to the respondents’ perceived importance of factors influencing their

intention to study at a HEI. In order words, the confirmatory factor analysis approach

was employed. In short, the validity test was demonstrated to test and ensure the

appropriateness of the instrument used in the present study.

4.7.4 Reliability Test

The reliability test of this instrument was examined through Cronbach’s Alpha

Coefficient. The objective of the reliability test was to ensure that the measurable

items of each variable were measuring the same underlying construct. If the results

reveal a high alpha value then the internal consistency of the set of items is

65

determined. Consequently, these items were eligible for making up the scale (be

computed) for the following analyses.

4.7.5 Relationship Approach

Two inferential analyses were carried out to investigate the relationship between the

proposed IVs and DV in the present study; Pearson’s correlation and multiple linear

regression. First, the correlation analysis was carried out to identify the significant

strength and direction of the linear relationship between the proposed IVs and DV.

Computed items under each variable and averaged variable score of IVs and DV were

subject to analysis using Pearson’s correlation.

Multiple linear regression analysis was performed to evaluate the prediction of

the DV from the six proposed IVs. Moreover, this analysis was used to indicate the

predictor and its contribution towards the criterion. In this study, the independent

variables were the suspected predictors and the dependent variable was the criterion.

4.7.6 Differences Approach

The t-test was used to compare the mean score of the continuous items. In the

analysis, the different groups of respondents were defined by their gender, male

respondents and female respondents. ANOVA was performed to compare the mean

score of three groups of respondents. In this section, the respondents were divided

into three different groups according to their academic background, namely, Form

six/STPM, GCE A-level, and others (comprising all other courses). The ultimate

objective of differential analyses is to identify which groups are significantly different

from one another on the proposed variables. The overall research approaches are

summarized in Table 4.3.

66

Table 4.3: The summary of analysis

Analysis Methodology Objective of Analysis Normality tests Graphical and statistical

normality tests To ensure the sample are normally distributed and the homoscedasticity of sample

Descriptive (A) Comparison of means Statistical description To compare the tendency of means for

measured items and variables (B) Rank ordering Statistical description To identify the orders of important factors

Validity test Factor Analysis To confirm the items were valid to measure

the underlying concept Reliability test Cronbach’s Alpha

Coefficient

To ensure the internal consistency of the measureable item scale

Relationship Approach (A) Relationships between

variables Pearson’s Correlation To identify the relationships between the

IVs and the DV (B) Predictors and its

contribution to criterion

Multiple Regression To determine the significant predictors and their contribution towards the criterion

Differences Approach (A) Difference between

gender Independent Sample t-test

To identify differences in important attributes between gender

(B) Difference between academic background

One-way ANOVA To identify differences in important attributes between academic backgrounds

4.8 Assumptions of the Study

There are other factors that may influence the students’ intention to study at a

HEI. However, other factors are not considered as significant factors as the impact

level may be negligible.

Students or respondents who participated in the survey are assumed to have a

high possibility and intention to further their study at a HEI.

All the respondents were assumed to understand the items in the questionnaire,

and answer honestly. As a result, the findings in this study represent real situations.

67

4.9 Conclusion of the Chapter

The research methodology employed in the present study was extensively discussed

in this chapter. The discussion included research design, sample selection and

sampling process, measurement design and the data analysis the study is going to

apply. The findings of these analyses are exhibited in Chapter 5.

CHAPTER 5

Data Analysis and Findings

5.1 Introduction

5.2 Result of Sampling

5.3 Respondents’ Profile

5.4 Normality Test

5.4.1 Histogram

5.4.2 Stem-and-leaf Plots

5.4.3 Boxplot

5.4.4 Descriptive Statistic

5.4.5 Summary of Normality Tests

5.5 Descriptive Analysis

5.6 Validity Test

5.6.1 Independent Variables

5.6.2 Dependent Variables

5.7 Reliability Test

5.8 Correlation Analysis

5.9 Multiple Regression Analysis

5.10 Independent Sample t-Test

5.11 One-way Analysis of Variance (One-way ANOVA)

5.12 Conclusion of the Chapter

Chapter 1 Introduction

Chapter 2 Literature Review

Chapter 3 Conceptual Model

Chapter 4 Research Methodology

Chapter 5 Data Analysis and

Findings

Chapter 6 Discussion and

Conclusion

5.1 Introduction 5.2 Result of Sampling 5.3 Respondents’ Profile 5.4 Normality Test 5.5 Descriptive Analysis 5.6 Validity Test 5.7 Reliability Test 5.8 Correlation Analysis 5.9 Multiple Regression Analysis 5.10 Independent Sample t-Test 5.11 One-Way Analysis of Variance 5.12 Conclusion of the Chapter

68

CHAPTER 5 DATA ANALYSIS AND FINDINGS

5.1 Introduction

This chapter presents the findings obtained from the analyses. The chapter begins

with the results of the sampling, which illustrates the sources of respondents from

various locations within the Klang Valley. The exact locations and response rate are

clearly indicated. The demographical data is shown in the respondents’ profile

section. Normality tests were performed to ensure the sample normality, then

descriptive analyses were performed for each item and variable. Two inferential

analyses were carried out, namely, Pearson’s correlation and multiple regression. The

bivariate analysis analyzes the relationship between the independent variables and the

dependent variable. Multiple regression analysis is to indicate its predictor and

criterion. In addition, differential analyses including independent t-test and One-Way

ANOVA were carried out to identify the difference between the respondents’ gender

and highest qualification (academic), respectively.

5.2 Result of Sampling

Questionnaires were distributed in the form of a survey to students currently at pre-

university level in the three selected sampling areas: tuition centres at Jalan Petaling,

International Islamic University Malaysia (UIAM) Matriculation Centre, and private

institutes at Wangsa Maju, Subang Jaya and Cheras. The entire sampling was

completed in approximately 22 days. A total of 800 questionnaires were distributed

and 522 responses were returned, contributing to a 65.25 percent response rate, which

is reasonably good. However, a total of 30 students’ responses were excluded from

69

analysis due to leaving one or more items blank. Eight responses were excluded due

to incorrect answers in their questionnaires. Another four responses from

undergraduate students were eliminated as they were not qualified as the targeted

sample for this study. The remaining 480 respondents accounted for 60.00 percent of

the total number of distributed questionnaires and were eventually used for analysis.

The report of sampling is shown in Table 5.1.

Table 5.1: The Detail of Sampling Result

Sampling Location

Number of Questionnaires

Distributed Return of

Questionnaire

Return of Questionnaire (Percentage)

Total Respondents

Subject to Analysis

(A) Pusat Tuisyen K (Jalan Petaling)

100 52 52.00 48 1.

(B) Pusat Tuisyen Y (Jalan Petaling)

100 77 77.00 72

2. International Islamic

University Malaysia Matriculation Centre (Petaling Jaya)

100 68 92.50 63

3. (A) Tunku Abdul

Rahman College, TARC (Wangsa Maju)

300 186 62.00 170

(B) Taylor University College (Subang Jaya)

100 84 84.00 78

(C) University College Sedaya International, UCSI (Cheras)

100 55 55.00 49

Total 800 522 65.25 480

70

5.3 Respondents’ Profile

The respondents’ demographical data is descriptively analyzed in this section. The

comprehensive demographical profiles of the respondents are shown in Table 5.2.

Female respondents outnumber male respondents in this sample, accounting

for 57.90 percent and 42.1 percent, respectively. The majority of the respondents are

from the 16-18 years (46.70%) age group and 19-21 years (49.60%), and no

respondents fall in the age group of 15 and below. Although there are some

respondents aged over 22 years the number is relatively small. As a result, this finding

manifests that the age range of pre-university level students in Malaysia is mostly

between 16 to 21 years old.

From the ethnic perspective, Chinese represented the highest number of

respondents (40.2%) among the ethnic groups, followed by Malay (33.1%), Indian

(25%), and others (1.7%). In the religion context, about 35.20 percent, 30.90 percent

and 22.80 percent of respondents were Buddhist, Muslim and Christian, respectively.

The majority of respondents come from small (1-4 persons) and average (5-6

persons) sized families. These family sizes account for 79.5 percent in this category.

Most respondents’ family gross monthly income is RM6,000 and below which

accounted for 86.6 percent, and the largest income group is in the range of RM2,001

to RM4,000 at 38.5 percent. This result indicates that most of the respondents have a

medium family monthly income level. The findings are graphically shown in Figure

5.1 to Figure 5.7.

71

Table 5.2: The Demographical Profiles of the Respondents (N = 480)

Frequency, n Percentage, %

Male 202 42.10 Gender Female 278 57.90

Total 480 100 15 years or below 0 0.00 16-18 years 224 46.70 19-21 years 238 49.60

Age Group

22 years and above 18 3.80 Total 480 100

Malay 159 33.10 Chinese 193 40.20 Indian 120 25.00

Ethnic Group

Others 8 1.70 Total 480 100

Muslim 164 34.20 Christian 104 21.70 Buddhist 130 27.10 Hindu 77 16.00

Religion

Others 5 1.00 Total 480 100

STPM/Form Six 160 33.3 GCE A-Level 160 33.3 Oversea Pre-U 60 12.5 Local Matriculation 63 13.1 University Foundation Programme 37 7.70

Highest Qualification (Including Currently Attending)

Others 0 0.00 Total 480 100

1-2 persons 16 3.30 3-4 persons 183 38.10 5-6 persons 183 38.10 7-8 persons 81 16.90

Family Size (Including Respondent)

Above 8 persons 17 3.50 Total 480 100

RM 2000 or less 137 28.50 RM 2001 – RM 4000 185 38.50 RM 4001 – RM 6000 94 19.60 RM 6001 – RM 8000 50 10.40 RM 8001 – RM 10000 8 1.70 RM 10001 and above 6 1.30

Family Gross Monthly Income

Total 480 100

72

Respondent's Gender

Female, n = 27857.9 %

Male, n = 20242.1 %

Figure 5.1: The gender group profile of the respondents

46.7% 49.6%

3.8%

0

50

100

150

200

250

Number of Students

16-18 years 19-21 years 22 years andabove

Year

Respondent's Age Group

Figure 5.2: The age group profile of the respondents

73

Respondent's Ethnic Group

Chinesen=193, 40.2%

Indiann=120, 25%

Malayn=159, 33.1%

Othersn=8, 1.7%

Figure 5.3: The ethnic group profile of the respondents

Figure 5.4: The profile of respondents’ religion

Respondent's Religion

Hindu n = 77, 16%

Buddhistn =130, 27.1%

Christiann=104, 21.7%

Muslimn=164, 34.2%

Othersn=5, 1%

74

Respondent's Highest Qualification (Including Currently Attending)

University Foundation Programmen =37, 8%Local

Matriculationn =63, 13%

OverseasPre-U

n =60, 13%GCE A-Leveln =160, 33%

STPM/ Form Six

n =160, 33%

Figure 5.5: The highest qualification status profile of the respondents

Figure 5.6: The family size profile of the respondents

3.3%

38.1% 38.1%

16.9%

3.5%

0 20 40 60 80

100 120 140 160 180 200

Number of Respondents

1-2persons

3-4persons

5-6persons

7-8persons

Above 8 persons

Family Size

Respondent's Family Size (Including Respondent)

75

3.3%

38.1% 38.1%

16.9%

3.5%

020406080

100120140160180200

Number of Respondents

1-2persons

3-4persons

5-6persons

7-8persons

Above 8persons

Family Size

Respondent's Family Size (Including Respondent)

Figure 5.7: The family gross monthly income profile of the respondents

76

5.4 Normality Test

According to Pallant (2007), normality is described by a symmetrical bell shaped

curve, which has the greatest frequency of scores in the middle, with smaller

frequencies towards the extremes. In this study, after exploration for the normality

tests, some potential outliers were found in the findings and then removed in

sequence. Hence, the total sample size was reduced from N = 522 to N = 480. The

normalized findings are shown in the following sub-chapters.

5.4.1 Histogram

All the scale type data shows a normally distributed curve in the histogram chart. The

findings indicate that the sample is normally distributed. The histogram is shown in

Appendix II.

5.4.2 Stem-and-leaf Plots

Stem-and-leaf plots of the collected data are emerging normal distributions; therefore

the sample is normally distributed. The result of the stem-and-leaf plots is shown in

Appendix II.

5.4.3 Boxplot

The potential outliers were counter checked by boxplot and all potential outliers were

eliminated. The boxplot of collected data is shown in Appendix II. The distribution

of the boxplot showing the sample is normally distributed after drawing the potential

outlier respondents’ data (normalization). Furthermore, no significant outliers were

revealed in the boxplot for the any of the variables.

77

5.4.4 Descriptive Statistics

The normality of the sample is deduced from the results of the Skewness and Kurtosis

tests. All the values are between -2 to +2, which fall in the normal range for the

Skewness and Kurtosis tests (Sekaran, 2003). Therefore, the normality of the sample

is acceptable. The details of the findings are reported in Table 5.3.

Table 5.3: Statistical normality tests for scale data from the sample (N = 480)

Cost of education

Degree (content

and structure)

Physical aspects,

facilities and resources

Value of Education

Institutional information

People (Family,

friends, peers and teachers)

Intention to study at a HEI

Mean 3.62 3.61 3.84 3.44 3.74 3.64 3.93 5% Trimmed Mean

3.62 3.62 3.85 3.44 3.73 3.65 3.93

Median 3.60 3.60 4.00 3.40 4.00 3.75 4.00 Variance 0.17 0.30 .145 .424 .241 .526 .288 Std. Deviation 0.41 0.54 0.38 0.65 0.49 0.73 0.54 Minimum 2.80 2.20 3.00 2.00 2.00 1.00 2.17 Maximum 4.40 5.00 4.50 5.00 5.00 5.00 5.00 Range 1.60 2.80 1.50 3.00 3.00 4.00 2.83 Skewness 0.18 -1.53 -1.77 0.50 -1.64 -1.44 -0.46 Kurtosis -1.84 -1.92 -1.14 -0.98 -0.97 1.76 1.12

5.4.5 Summary of Normality Tests

All the normality tests (histogram, stem-and-leaf plots, boxplot, and descriptive

statistics shows the data are normally distributed. The results of the tests are

summarized in Table 5.4.

Table 5.4: Summary of normality tests of the sample (N = 480)

Test Normal Distribution of Sample Histogram Support Stem-and-leaf Plots Support Boxplot Support Descriptive Statistic (Skewness and Kurtosis) Support

78

The overall results indicate that the distribution of the sample is normal.

Hence, the sample is acceptable and can be considered as normally distributed and

randomly selected from the population. The importance of the determination of the

sample’s normality is to ensure its homoscedasticity. The residual between the

observed value and the predicted value must be small enough so that the model fits

the sample indicating that the sample is representative of the population.

5.5 Descriptive Analysis

The summary of the means for the 42 items according to each variable is shown in

Table 5.5. All the items have a mean score of above 3.00. Thus, the findings indicate

that the majority of the respondents agreed with the statement of items for each

variable, and considered those items important for their intention to study at a HEI.

Table 5.5: Summary of the mean of items according variable (N = 480)

Importance Variable Mean S.D.

Cost of education(IV1) C1 Provide education at a reasonable cost 3.63 0.61 C2 Make financial aid available to its students 3.62 0.65 C3 Make scholarships available to its students. 3.59 0.69 C4 Make flexible payment of fee to its students 3.63 0.61 C5 Make accommodation available to its students at reasonable cost 3.63 0.60

Degree (Content and Structure) (IV2) D1 Have reasonable entry requirements for its programmes 3.64 0.68 D2 Provide a wide range of courses for students to select from 3.57 0.82

D3 Provide students flexibility in selecting courses/subjects during their study 3.56 0.75

D4 Provide students with a number of specialized programmes to suit their needs 3.64 0.72

D5 Offer degrees with reasonable completion periods of study 3.63 0.70 Note: Importance score: 5 = maximum, 1 = minimum

79

Importance Variable Mean S.D.

Physical Aspects, Facilities and Resources (IV3) P1 Be situated in an ideal location 3.87 0.49 P2 Provide students with an environment that is conductive to learning 3.82 0.56 P3 Provide students with great recreation and other facilities 3.94 0.48 P4 Provide students with an expected social life on campus 3.83 0.51

P5 Provide students with all the necessary resources that are required for their education 3.84 0.51

P6 Provide students with a clean study environment 3.72 0.56 P7 Provide students with a safe condition for study 3.86 0.51 P8 Have exceptional quality of faculty members 3.83 0.50

Value of Education (IV4) V1 Well known for the reputation 3.49 0.79 V2 Well known for their academic value 3.41 0.87 V3 Well recognized by other academic institutions 3.37 0.81 V4 Well recognized by professional bodies 3.46 0.77 V5 Well recognized by respected industries 3.48 0.76 Institutional Information (IV5) I1 Provide students with information regarding application processes 3.73 0.54 I2 Make information easily available to students from time to time 3.72 0.54 I3 Provide students with information regarding career opportunities 3.76 0.51 I4 Provide students with information regarding their area of study 3.78 0.55 I5 Provide students with information regarding post-graduate studies 3.71 0.58

People (Family, Friend, Peers and Teachers )(IV6) F1 I usually rely on my family members’ opinion. 3.68 0.81 F2 My family views on the HEI are important. 3.65 0.80 F3 I usually rely on my friends’ advice. 3.68 0.82 F4 My friends’ perceptions towards the HEI are important. 3.52 0.90 F5 I usually rely on my peers’ idea. 3.67 0.80 F6 My peers’ suggestions are vital. 3.52 0.92 F7 I usually rely on my teachers’ view. 3.71 0.80 F8 My teachers’ recommendations are vital. 3.66 0.85

Intention to Study at a Higher Educational Institution (DV) S1 The likelihood of furthering my study at a HEI is high. 4.08 0.70 S2 I have a strong interest in pursuing my study at a HEI. 3.90 0.72 S3 I will recommend the HEI I choose to my friends. 3.75 0.81 S4 I will say favourable things about the HEI I chose. 4.05 0.70 S5 I am willing to spend to study at a HEI. 3.95 0.70 S6 I am willing to pay a high rate for the HEI I chose. 3.84 0.85

Note: Importance score: 5 = maximum, 1 = minimum

80

A summary of the computed means of all the items according to the variables

is shown in Table 5.6. The overall scores for each variable were obtained by

averaging the response to the appropriate items.

Table 5.6: Summary of the means of computed items according to variable (N = 480)

Importance Variable Mean S.D.

Cost of Education 3.62 0.41 Degree (Content and Structure) 3.61 0.55 Physical Aspects, Facilities and Resources 3.84 0.38 Value of Education 3.44 0.65 Institutional Information 3.74 0.50 People (Family, Friends, Peers and Teachers) 3.64 0.73 Intention to Study 3.93 0.54

The means of all computed items are above 3.00. This result indicates that the

respondents consider all the factors listed above have some importance regarding their

intention to continue their studies at a HEI.

The results of ranking the important factors influencing students’ intention to

study at a higher educational institute are shown in Table 5.7.

Table 5.7: The ranking order of each important factor (N = 480)

Variable Rank (I) Number of

respondent, n Score (I × n)

Cost of Education (IV1) 1 240 240 2 99 198 3 79 237 4 24 96 5 14 70 6 24 144 Total 985 Degree (Content and Structure) (IV2) 1 35 35 2 60 120 3 49 147 4 155 620 5 92 460 6 89 534 Total 1916

81

Variable Rank (I) Number of

respondent, n Score (I × n)

1 92 92 Physical Aspects, Facilities and Resources (IV3) 2 78 156 3 197 591 4 76 304 5 25 125 6 12 72 Total 1340 Value of Education (IV4) 1 28 28 2 29 58 3 46 138 4 101 404 5 215 1075 6 61 366 Total 2069 Institutional Information (IV5) 1 15 15 2 31 62 3 30 90 4 104 416 5 116 580 6 184 1104 Total 2267

1 69 69 People (Family, Friends, Peers and Teachers) (IV6) 2 185 370 3 78 234 4 21 84 5 17 85 6 110 660 Total 1502

In order to obtain the score for each factor, the ranking was multiplied by the

number of respondents accordingly. Thus, the sum score of each factor was obtained.

The scores were sorted in ascending order (from low to high), with the lowest score

indicating the first rank, and the highest score indicating the last rank. The result of

this analysis is shown in Table 5.8.

82

Table 5.8: The overall score of each factor ranked by respondents (N = 480)

Rank Variable Total Score 1 Cost of Education 985 2 Physical Aspects, Facilities and Resources 1340 3 People (Family, Friends, Peers and Teachers) 1502 4 Degree (Content and Structure) 1916 5 Value of Education 2069 6 Institutional Information 2267

In summary, in ranking order analysis, cost of education, physical aspects,

facilities and resources of the HEI, and the people factor such as influences from

family members, friends, peers, and teachers, are the three that students perceive as

the most important factors influencing their intention to study at a HEI.

5.6 Validity Test

The validity test is used to determine that the questions in the questionnaire are

tapping the right concept and not something else (Sekaran, 2003). Validity tests

determine how well an instrument measures the particular concept it is supposed to

measure. Pallant (2007) cited that there are two main issues to consider in determining

whether a particular data set of a sample is appropriate for factor analysis; sample size

and the strength of the relationship among the items or variables. For sample size,

Tabachnick and Fidell (2007) suggested that it is comforting to have at least 300 cases

for factor analysis. The sample size of this study is 480, which exceeds the minimum

number required, therefore, the data set for the sample is acceptable for factor

analysis. The validity test is performed through factor analysis. Factor analysis is

carried out to validate the appropriateness of the measureable items used in this study.

83

The strength of the inter-correlation among the items must also be considered.

According to Tabachnick and Fidell (2007), a correlation coefficient (loading level)

greater than 0.3 is considered acceptable for analysis. Based on the result of factor

analysis, a total of 36 items listed in the independent variables were included. An

inspection of the correlation matrix revealed the presence of many coefficients of 0.3

and above, see Appendix III.

Two statistical measures were also carried out to determine the ability to

perform factor analysis. In other words, the suitability of data for factor analysis was

assessed. First, the Kaiser-Meyer-Olkin (KMO) measure of sampling adequacy, and

Bartlett’s test of Sphericity. According to Tabachnick and Fidell (2007), Bartlett’s test

of Sphericity should be significant (p < 0.05) in order for the factor analysis to be

considered appropriate, while the minimum value for a good factor analysis is 0.60

for the Kaiser-Meyer-Olkin (KMO) index (Pallant, 2007). In this section, two factor

analyses were carried out separately for the independent variables and the dependent

variable.

5.6.1 Independent Variables

The results of the KMO and Bartlett’s Test for independent variable are shown in

Table 5.9. The Kaiser-Meyer-Olkin value is 0.81, exceeding the value of 0.60 (Kaiser

1970, 1974), and Bartlett’s Test of Sphericity (Bartlett 1954) is statistically significant

(P < 0.00), supporting the factorability of the correlation matrix.

Table 5.9: KMO and Bartlett’s Test for independent variable

Kaiser-Meyer-Olkin Measure of Sampling Adequacy. .805Bartlett's Test of Sphericity Approx. Chi-Square 15358.357 df 630 Sig. .000

84

In the principal components analysis (PCA), a total of 36 items listed under

independent variables were subjected to analysis. The results reveal the presence of

seven components with eigenvalues exceeding 1, explaining 19.3%, 14.5%, 12.6%,

10.5%, 7.0%, 4.1%, and 2.9% of the variance, respectively, as shown in Table 5.10.

An inspection of the scree plot (Figure 5.8) revealed a clear break after the sixth

component. Furthermore, the Parallel Analysis showed only six components with

eigenvalues exceeding the corresponding criterion values for a randomly generated

data matrix of the same size of data (36 items × 480 respondents). Therefore, six

components are accepted as appropriate factors in this study. These findings are

shown in Table 5.11 and Table 5.12.

Component Number363534333231302928272625242322212019181716151413121110987654321

Eig

enva

lue

6

4

2

0

Scree Plot

Figure 5.8: Screen plot between eigenvalue and number of factors

85

Table 5.10: Total variance explained for independent variables

Component Initial Eigenvalues Extraction Sums of Squared

Loadings

Total % of

Variance Cumulative

% Total % of

Variance Cumulative

% 1 6.948 19.301 19.301 6.948 19.301 19.3012 5.345 14.848 34.149 5.345 14.848 34.1493 4.542 12.618 46.767 4.542 12.618 46.7674 3.790 10.529 57.296 3.790 10.529 57.2965 2.521 7.004 64.300 2.521 7.004 64.3006 1.491 4.142 68.442 1.491 4.142 68.4427 1.044 2.901 71.344 1.044 2.901 71.3448 .954 2.651 73.994 9 .904 2.510 76.504 10 .775 2.151 78.656 11 .748 2.077 80.732 12 .668 1.856 82.588 13 .631 1.752 84.339 14 .574 1.596 85.935 15 .540 1.499 87.434 16 .521 1.447 88.881 17 .481 1.336 90.217 18 .460 1.278 91.495 19 .403 1.121 92.615 20 .359 .997 93.612 21 .342 .950 94.562 22 .274 .761 95.324 23 .244 .677 96.001 24 .220 .610 96.611 25 .180 .499 97.109 26 .165 .457 97.567 27 .146 .406 97.973 28 .128 .356 98.329 29 .117 .325 98.655 30 .100 .278 98.933 31 .093 .258 99.190 32 .080 .221 99.412 33 .063 .176 99.587 34 .055 .152 99.740 35 .053 .148 99.888 36 .040 .112 100.000

Extraction Method: Principal Component Analysis.

86

Table 5.11: Output from parallel analysis

Number of variables: 36 Number of subjects: 480 Number of replications: 100 (specify) Eigenvalue # Random Eigenvalue Standard Dev 1 1.5541 .0391 2 1.4855 .0277 3 1.4341 .0260 4 1.3931 .0243 5 1.3514 .0201 6 1.3160 .0185 7 1.2819 .0172 8 1.2506 .0185 9 1.2219 .0173 10 1.1912 .0169 11 1.1634 .0142 12 1.1380 .0166 13 1.1120 .0146 14 1.0854 .0146 15 1.0625 .0129 16 1.0403 .0138 17 1.0156 .0141 18 0.9910 .0137 19 0.9663 .0111 20 0.9446 .0116 21 0.9214 .0136 22 0.8980 .0125 23 0.8745 .0141 24 0.8516 .0144 25 0.8312 .0141 26 0.8091 .0143 27 0.7862 .0133 28 0.7666 .0140 29 0.7441 .0120 30 0.7207 .0123 31 0.6970 .0134 32 0.6740 .0144 33 0.6475 .0169 34 0.6226 .0153 35 0.5963 .0157 36 0.5604 .0214 Monte Carlo PCA for Parallel Analysis

Table 5.12: Comparison of eigenvalue from PCA and criterion values from parallel analysis

Component

Number Actual Eigenvalue

from PCA Criterion value from

Parallel Analysis Decision

1 6.948 1.5541 Accept 2 5.345 1.4855 Accept 3 4.542 1.4341 Accept 4 3.790 1.3931 Accept 5 2.521 1.3514 Accept 6 1.491 1.3160 Accept 7 1.044 1.2819 Reject

87

Table 5.13: Rotation component matrix result for independent variables

Component 1 2 3 4 5 6 F1 I usually rely on my family members' opinion .932 F5 I usually rely on my peers' idea .909 F8 My teachers' recommendations are vital .897 F4 My friends' perceptions towards the HEI are important .891 F7 I usually rely on my teachers' view .880 F3 I usually rely on my friends' advice .873 F6 My peers' suggestions are vital .862 F2 My family’s view on the HEI is important .647

D4 Provide students with a number of specialized programmes to suit their needs .785

D3 Provide students flexibility in selecting courses/subjects during their study .776

D2 Provide a wide range of courses for students to select from .753

D5 Offer degrees with reasonable completion periods of study .618

D1 Have reasonable entry requirements for its programmes .597 P7 Provide students with a safe condition for study .873

P5 Provide students with all the necessary resources that are required for their education .870

P4 Provide students with an expected social life on campus .837

P2 Provide students with an environment that is conductive to learning .809

P1 Be situated in an ideal location .784 P6 Provide students with a clean study environment .645 P8 Have exceptional quality of faculty members .622 P3 Provide students with great recreation and other facilities .394

I1 Provide students with information regarding application processes .949

I2 Make information easily available to students from time to time .933

I5 Provide students with information regarding post-graduate studies .901

I4 Provide students with information regarding their area of study .888

I3 Provide students with information regarding career opportunities .813

V5 Well recognized by respected industries .743 V4 Well recognized by professional bodies .740 V1 Well known for the reputation .663 V2 Well known for their academic value .442 V3 Well recognized by other academic institutions .328 C2 Makes financial aid available to its students .787 C3 Make scholarships available to its students .731

C5 Make accommodation available to its students at reasonable cost .407

C1 Provide education at a reasonable cost .349 C4 Make flexible payment of fee to its students .329

88

A complete rotation component matrix result for independent variables is

shown in Table 5.13. Only items with a factor loading value greater than 0.30 were

considered. Based on the results, there are six identified factors as follows:

Component Factor 1 People (Family, Friends, Peers and Teachers) 2 Degree (Content and Structure) 3 Physical Aspects, Facilities and Resources 4 Institutional Information 5 Value of Education 6 Cost of Education

Factor 1 includes “I usually rely on my family members’ opinion”, “I usually

rely on my peers’ idea”, “My teachers’ recommendations are vital”, “My friends’

perceptions towards the HEI are important”, “I usually rely on my teachers’ view”, “I

usually rely on my friends’ advice”, “My peers’ suggestions are vital”, and “My

family views on the HEI are important”. All the proposed eight items are categorized

under the independent variable called “People (family, friends, peers, and teachers)”.

Factor 2 contains four items, they are “Provide students with a number of

specialized programmes to suit their needs”, “Provide students flexibility in selecting

courses/subjects during their study”, “Provide a wide range of courses for students to

select from”, and “Offer degrees with reasonable completion periods of study”. These

items fall into the independent variable named “Degree (Content and Structure)”.

Nonetheless, there are five items under this variable in the instrument. “Have

reasonable entry requirements for its programmes” was not included as its factor

loading was less than 0.60.

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There are seven items in Factor 3, namely, “Physical Aspects, Facilities and

Resources”. It consists of “Provide students with a safe condition for study”, “Provide

students with all the necessary resources that are required for their education”,

“Provide students with an expected social life on campus”, “Provide students with an

environment that is conducive to learning”, “Be situated in an ideal location”,

“Provide students with a clean study environment”, and “Have exceptional quality of

faculty members”.

Factor 4 comprises “Provide students with information regarding application

processes”, “Make information easily available to students from time to time”,

“Provide students with information regarding post-graduate studies”, “Provide

students with information regarding their area of study”, and “Provide students with

information regarding career opportunities”. This factor is categorized as

“Institutional Information”. All items within this variable have relatively high loading

value compared to other variables, with above 0.80.

Items such as “Well recognized by respected industries”, “Well recognized by

professional bodies”, and “Well known for the reputation” are included in factor 5,

which is classified as “Value of Education”. Factor 6 consists of “Make financial aid

available to its students” and “Make scholarships available to its students”. These two

items are categorized under the variable of “Cost of Education” in this study.

In general, the overall results of factor analysis for the independent variables is

reasonable, and supports the proposed questionnaire. The identified six factors

accounted for 68.44% of the total variance explained. Thus, this finding revealed an

acceptable result, as all the proposed items of the independent variables in the

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instrument are valid; it means the measurement measured what it is supposed to

measure in this study.

5.6.2 Dependent Variables

The results of the KMO and Bartlett’s Test for independent variable are shown in

Table 5.14. The Kaiser-Meyer-Olkin value is 0.75, exceeding the minimum value of

0.60 (Kaiser 1970, 1974), and Bartlett’s Test of Sphericity (Bartlett 1954) reached

statistically significant, supporting the factorability of the correlation matrix.

Table 5.14: KMO and Bartlett’s Test for dependent variable

Kaiser-Meyer-Olkin Measure of Sampling Adequacy. .750Bartlett's Test of Sphericity Approx. Chi-Square 1282.916 df 15 Sig. .000

In the principal components analysis (PCA), a total of six items listed under

dependent variable were subjected to analysis. Results revealed only the components

with eigenvalues exceeding 1, explaining 54.2% of the variance; these are shown in

Table 5.15. Furthermore, an inspection of the scree plot shown in Figure 5.9 revealed

a clear break after the first component. A complete component matrix result for

dependent variables is shown in Table 5.16. The results clearly indicate that only one

factor was measured from the items in the dependent variable, which is “Intention to

study at a HEI”. This factor comprises five items comprising “The likelihood to

further my studies at HEI is high”, “I am willing to spend for studying in a HEI”, “I

will say favourable things about the HEI I chose”, “I am willing to pay at a high rate

for the HEI I choose”, and “I have a strong interest to pursue my studies at a HEI”

91

Table 5.15: Total variance explained for items in dependent variable

Component Initial Eigenvalues Extraction Sums of Squared

Loadings

Total % of

Variance Cumulative

% Total % of

Variance Cumulative

% 1 3.254 54.229 54.229 3.254 54.229 54.2292 .981 16.357 70.587 3 .756 12.606 83.193 4 .518 8.635 91.828 5 .323 5.387 97.215 6 .167 2.785 100.000

Extraction Method: Principal Component Analysis.

Table 5.16: Component matrix result for dependent variable

Component 1 The likelihood to further my study at HEI is high .876 I am willing to spend for studying in a HEI .822 I will say favourable things about the HEI I chose .809 I am willing to pay at a high rate for the HEI I choose .696 I have a strong interest to pursue my studies at a HEI .696

Component Number654321

Eige

nval

ue

4

3

2

1

0

Scree Plot

Figure 5.9: Screen plot for items in dependent variable

92

In conclusion, the measureable items performed in this study reflect the

validity of the instruments, as well as the defined variables. Hence, this instrument is

acceptable to measure the population as the proposed concepts are aligned with the

objective in this research.

5.7 Reliability Test

Reliability is concerned with estimates of the degree to which a measurement is free

of random or unstable error (Donald and Pamela, 2003). Besides, the reliability of a

measure indicates the extent to which it is without bias (error free) and, hence, ensures

consistent measurement across time and across the various items in the instruments.

The reliability of the scales instrument employed in this study was investigated

through the Cronbach’s alpha coefficient test.

The reliability of a measure is an indication of the stability and consistency of

the extent that the instrument measures the concept and helps to assess the “goodness”

of a measure (Sekaran, 2003). Briefly, reliability tests show how consistently a

measuring instrument measures a particular concept.

There are two frequently used indicators of a scale’s reliability in research;

they are the test-retest reliability and internal consistency. Test-retest reliability is

concerned with the reliability coefficient obtained with a repetition of the same

measure on a second occasion (Sekaran, 2003). Whereas the internal consistency

refers to the degree to which the items that make up the scale are all measuring the

same underlying attribute (Pallan, 2003).

93

In this study, Cronbach’s alpha coefficient was used to measure the internal

consistency of the scales employed in this survey. The Cronbach’s alpha value for

each variable is shown in Table 5.17.

Table 5.17: Cronbach’s alpha value of variables

Variable

Number of item

Cronbach’s alpha Value

IV Cost of Education 5 0.65 IV Degree (Content and Structure) 5 0.80 IV Physical Aspects, Facilities and Resources 8 0.88 IV Value of Education 5 0.87 IV Institutional Information 5 0.93 IV People (Family, Friends, Peers and Teachers) 8 0.95 DV Intention to study at a HEI 6 0.82

Table 5.17 shows that all the variables except the “cost of education” revealed

Cronbach’s alpha Values greater than 0.80. As Nunnally (1978) and DeVellis (2003)

recommend a minimum level of 0.70, the scale of the six variables can be considered

as having high reliability. Also, the Cronbach’s alpha values are dependent on the

number of items. Pallant (2007) cited that when there are a small number of items in

the scale, for instance fewer than ten items, it is common to find low Cronbach’s

alpha values (i.e. 0.50).

The results show that those items under the variable of “cost of education”

contribute a Cronbach’s alpha value of 0.65, which is lower than the minimum level

of 0.70. In this case, it is more appropriate to report the mean inter-item correlation

for the items within the variable, see Table 5.18.

Briggs and Cheek (1986) recommend an optimal range for the inter-item

correlation of 0.20 to 0.40. Accordingly, half of the mean value of items within the

94

variable fall within this optimal range. Additionally, a minimum Cronbach’s alpha

value cut-off point of 0.60 is common in social-science research (Cohen, 1988). As a

result, the scale of this variable is acceptable to be considered as reliable in this study.

Table 5.18: Inter-Item Correlation Matrix for variable: Cost of Education

Provide education

at a reasonable

cost

Make financial aids available to its

students

Make scholarships

available to its students

Make flexible payment of fee to

its students

Make accommodation available to its

students at reasonable cost

Provide education at a reasonable cost 1.000 .215 .195 .125 .258

Make financial aids available to its students

.215 1.000 .472 .242 .212

Make scholarships available to its students

.195 .472 1.000 .360 .212

Make flexible payment of fee to its students

.125 .242 .360 1.000 .435

Make accommodation available to its students at reasonable cost

.258 .212 .212 .435 1.000

In conclusion, the findings of both the validity and the reliability tests support

the appropriateness of the instrument used throughout this study. In other words, the

items in the variables are valid and reliable to measure the concept that they are

supposed to measure. Therefore, the outcome of the instrument is suitable for a higher

level of analyses such as inferential and differential analysis.

95

5.8 Correlation Analysis

In this section, Pearson’s correlation is used to explore the relationship between the

independent variables (IVs) and the dependent variable (DV). Correlation coefficients

are able to provide a numerical summary of the direction and the strength of the linear

relationship between the IVs and the DV. Pearson’s correlation coefficients (r) range

from -1 to +1 and the sign in front indicates whether there is a positive or negative

correlation. The size of the absolute value provides information on the strength of the

relationship (Pallant, 2007). The findings of correlations between the independent

variables and the dependent variable are summarized in Table 5.19.

Table 5.19: The correlations between the independent variables and the dependent

variable (N =480)

Intention to study, DV

Cost of education, IV1 Pearson’ Correlation 0.11** Sig. (2-tailed) 0.02 Degree (content and structure), IV2 Pearson Correlation 0.20** Sig. (2-tailed) 0.00 Physical aspects, facilities and resources, IV3 Pearson Correlation 0.09** Sig. (2-tailed) 0.04 Value of education, IV4 Pearson Correlation 0.18** Sig. (2-tailed) 0.00 Institutional information, IV5 Pearson Correlation 0.10** Sig. (2-tailed) 0.03 People (Family, friends, peers and teachers, IV6 Pearson Correlation 0.16** Sig. (2-tailed) 0.00 ** Correlation is significant at the 0.01 level (2-tailed).

Cost of education (IV1)

There is a significant, weak and positive correlation between the Cost of Education

and the Intention to Study at a Higher Educational Institution (r = 0.11, p < .01). This

correlation shows that the more reasonable the cost of education offered by a higher

96

educational institute, the higher the students’ intention to further their study at the

institute.

Degree (Content and Structure) (IV2)

Similar to the cost of education, there is a significant, weak and positive correlation

between the Degree (Content and Structure and the Intention to Study at a Higher

Educational Institution (r = 0.20, p < .01). This correlation indicates that a higher

educational institute that is able to provide students with a wide range of courses and

more specialist programmes will attract more students’ intention to further their study

at the institute.

Physical Aspects, Facilities and Resources (IV3)

There is a significant, weak and positive correlation between the Physical Aspects,

Facilities and Resources and the Intention to Study at a Higher Educational Institution

(r = 0.09, p < .01). This correlation reveals that the better the physical aspects and

facilities provided by a higher educational institute to its students the more able it is to

retain more students’ intention to study at the institute.

Value of Education (IV4)

There is a significant, weak and positive correlation between the Value of Education

and the Intention to Study at a Higher Educational Institution (r = 0.18, p < .01). This

correlation shows that the higher the possibility that a higher educational institute has

a good reputation and ability to deliver high academic value in their programme, the

higher the students’ intention to continue their study at the institute.

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Institutional Information (IV5)

The correlation between the Institutional Information and the Intention to Study at a

Higher Educational Institution is significant, weak and positive (r = 0.10, p < .01).

This correlation indicates that the higher the ability of a higher educational institute to

provide comprehensive and relevant information regarding study, the students are

more likely to further their study at the institute.

People (Family, Friends and Peers and Teachers) (IV6)

There is a significant, weak and positive correlation between the People (Family,

Friends and Peer) and the Intention to Study at a Higher Educational Institution (r =

0.16, p < .01). This correlation shows that the higher the influence of the respondents’

significant people such as family members, friends, peers and teachers, the higher the

students’ intention to continue their study at the institute.

5.9 Multiple Regression Analysis

In this section, a multiple regression analysis was performed to determine the

predictor and its contribution towards the criterion. In other words, it is to find out the

prediction of a single dependent continuous variable from a group of independent

variables.

In order to ensure the appropriateness of the outputs from the regression

analysis, the assumptions of multiple regression must comply. In this case, the

normality, linearity, homoscedasticity, multicollinearity, autocorrelation, and

multivariate outlier, all refer to the various aspects of the distribution of scores and the

nature of the underlying relationship between the variables. These assumptions were

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checked by inspecting the Normal Probability Plot (P-P) of the Regression Standard

Residual, Scatter plot, and other tests that complement the regression analysis.

According to the histogram of the intention to study at a higher educational institution

(see Appendix II), the data of the dependent variable is normally distributed. Hence,

it ensures the normality of the sample. In addition, sample normality is further

demonstrated by a Normal P-P of the Regression Standard Residual, as shown in

Figure 5.10.

Observed Cum Prob1.00.80.60.40.20.0

Expe

cted

Cum

Pro

b

1.0

0.8

0.6

0.4

0.2

0.0

Normal P-P Plot of Regression Standardized Residual

Dependent Variable: Intention to Study at a Higher Educational Institution (HEI)

Figure 5.10: Normal P-P Plot of regression standardized residual for dependent

variable

In the Normal P-P plot, points are laid in a reasonably straight diagonal line

from bottom left to top right. It indicates no major deviation from normality.

99

On the other hand, from the scatted plot of residuals in Figure 5.11, the

residuals are roughly rectangularly distributed, with most of the scores concentrated in

the centre along the 0 axes. (red line). The findings indicate that the predictors

(independent variables) are linearly related to the residual of the criterion (dependent

variable). Therefore, the homoscedasticity of the sample is ensured. The findings

show that no outliers are detected as no score has a standardized residual of more than

3.3 or less than -3.3.

Regression Standardized Predicted Value3210-1-2-3

Regr

essi

on S

tand

ardi

zed

Resi

dual

2

0

-2

-4

Scatterplot

Dependent Variable: Intention to Study at a Higher Educational Institution (HEI)

Figure 5.11: The scatter plot of residuals observed value and predicted value

In addition, in the collinearity statistic tests all three predictors have tolerance

values greater than 0.10, and variance inflection factor, (VIF) values less than 10. It

reveals that there is no multicollinearity between the variables. The Durbin-Watson

value in this analysis is 1.54, which falls in the range of 1.5 to 2.5, indicating that

100

there is no autocorrelation in the residual. The Mahalanobis adjustment is performed

to encounter the potential multivariate outliers in the computed data. In conclusion, all

the assumptions were complied with throughout the regression analysis. Hence, the

appropriateness of these findings is ensured.

After all the assumptions were complied with, the multiple regression analysis

was carried out. The results of the multiple regression are shown in Table 5.20 to

Table 5.22.

Table 5.20: Multiple correlation of independent variables with dependent variable

Model Summaryd

Change Statistics

Model R R Square Adjusted R Square

Std. Error of the Estimate

R Square Change F Change df1 df2

Sig. F Change

Durbin-Watson

1 .199(a) .040 .038 .52625 .040 19.684 1 478 .0002 .245(b) .060 .056 .52120 .020 10.314 1 477 .0013 .281(c) .079 .073 .51646 .019 9.788 1 476 .002 1.544

a. Predictors: (Constant), Degree (Content and Structure) b. Predictors: (Constant), Degree (Content and Structure), People (Family, Friends, Peers and Teachers) c. Predictors: (Constant), Degree (Content and Structure), People (Family, Friends, Peers and Teachers), Cost of Education d. Dependent Variable: Intention to Study at a Higher Educational Institution (HEI)

There are multiple correlations (R =.28) of three significant predictors with the

criterion (dependent variable), as shown in Table 5.22. From the model, factors that

influence students’ intention to study at a HEI are degree (content and structure),

people (family, friends, peers and teachers), and cost of education. The three factors

have a significant effect size that explains 7.90 percent of the variability towards the

intention to study at a HEI. The adjusted R2 indicates that in the population, the three

factors account for 7.30% of the variance in respondents’ intention to study at a HEI.

101

A total of 92.70% of the variance of the criterion is unaccounted for. Table 5.21

reveals this regression is significant (F3, 476 = 13.58, p < .01).

Table 5.21: Significances of Independent variables

ANOVAd

Model Sum of Squares df Mean Square F Sig.

3 Regression 10.864 3 3.621 13.576 .000(c)

Residual 126.966 476 .267

Total 137.830 479 c. Predictors: (Constant), Degree (Content and Structure), People (Family, Friends, Peers and

Teachers), Cost of Education d. Dependent Variable: Intention to Study at a Higher Educational Institution (HEI)

Table 5.22: Regression coefficients and significance of independent variables

Coefficientsa

Unstandardized

Coefficients Standardized Coefficients

Collinearity Statistics

Model B

Std. Error Beta t Sig. Tolerance VIF

3 (Constant) 1.998 .377 5.296 .000 Cost of Education .178 .082 .136 2.160 .031 .492 2.032 Degree (Content and Structure) .192 .075 .196 2.562 .011 .331 3.018

Physical Aspects, Facilities and Resources .052 .064 .037 .802 .423 .933 1.071

Value of Education -.007 .066 -.009 -.108 .914 .303 3.297 Institutional Information .008 .060 .008 .140 .889 .641 1.560 People (Family, Friends, Peers and

Teachers) .107 .034 .145 3.192 .002 .947 1.056

a. Dependent Variable: Intention to Study at a Higher Educational Institution (HEI)

Table 5.22 indicates that only three significant predictors out of six

independent variables are positively related to the criterion in the regression. They are

degree (content and structure), IV2 (t = 4.40, p <.01), People (Family, Friends, Peers

and Teachers), IV6 (t = 3.42, p <.01), and Cost of Education, IV1 (t = 1.81, p <.05).

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The degree (content and structure) has the highest regression coefficient, 0.19

(95% CI = 0.11 to 0.28), followed by people (family, friends, peers and teachers),

0.18 (95% CI = 0.05 to 0.18), and cost of education, 0.11 (95% CI = 0.07 to 0.30).

[Confidence level, CI please refer to Appendix III] Effects from other predictors are

insignificant in this set of combinations, and those factors are not included in the

multiple regression equation. Therefore the multiple regression equation is as follows:

DV = 2.00 + 0.18 IV1 + 0.19 IV2 + 0.11 IV6

Where,

DV = Intention to study at a HEI.

IV1 = Cost of Education

IV2 = Degree (Content and Structure)

IV6 = People (Family, Friends, Peers and Teachers)

The beta value indicates that one unit increase in degree (content and

structure) will result in an increase in the respondents’ intention to study by 0.19

units. If the influences from significant people such as family, friends, peers and

teachers increases by one unit, the respondents’ intention to study will increase by

0.11 units. If the reasonability of cost of education increases by one unit, respondents’

intention to study will increase by 0.19 units. The relationship and implications are

further discussed in Chapter 6.

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5.10 Independent Sample t-test

An independent sample t-test was carried out to identify the differences between

respondents’ gender on the perceived importance of factors that influence their study

intention towards a HEI. The results of the independent sample t-test are shown in

Table 5.23.

Table 5.23: Independent sample t-test result for male and female respondent towards

proposed variables

Variable

Male ( N = 202)

Female ( N = 278) t P < .05

Cost of Education Mean 3.56 3.66 -2.83 Sig S.D. 0.41 0.40 Degree (Content and Structure) Mean 3.64 3.58 1.11 NS S.D. 0.51 0.57

Mean 3.79 3.87 -2.46 Sig Physical Aspects, Facilities and Resources S.D. 0.40 0.36 Value of Education Mean 3.39 3.48 -1.67 Sig S.D. 0.59 0.69 Institutional Information Mean 3.76 3.72 -0.75 NS S.D. 0.51 0.48

Mean 3.57 3.68 -1.69 NS People (Family, Friends, Peers and Teachers) S.D. 0.65 0.78 Intention to Study Mean 3.79 4.03 -4.77 Sig

S.D. 0.51 0.53

* Note: S.D. = Standard Deviation, Sig = Significant, NS = Not Significant

According to Table 5.23, four out of seven variables are significantly different

between the gender of the respondent’s. These variables are cost of education,

physical aspects, facilities and resources, value of education, and intention to study.

The other three variables – degree (content and structure), institutional information,

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and people (family, friends, peers, and teachers) remain insignificant. Furthermore,

the findings show that all variables have a small effect size.

In terms of cost of education, female respondents exhibit a higher mean score

than male respondents. This indicates that female students place more importance on

the cost of education in their HEI choice compared to male students. Furthermore, the

results reveal similar outcomes to the cost of education for three other variables:

physical aspects, facilities and resources, value of education, and intention to study.

Female students tend to be more concerned with these attributes, which affect their

HEI selection. The result is supported by findings from previous studies; females are

more comprehensive in evaluating information and often consider more attributes

than males in their decision making (Meyers-Levy et al., 1991). Moreover, the

findings show that female students have a relatively high willingness to further their

study to tertiary level. The further discussions are presented in Chapter 6.

5.11 One-way Analysis of Variance (One-way ANOVA)

In this study, One-way ANOVA was used to investigate the significant difference

between respondents’ academic background on perceived importance of factors that

influence their study intention towards a HEI. The use of One-way ANOVA is to

compare the variance between the different groups of respondents’ academic

background with the variability within each of the groups (analysis of variance).

In general, One-way ANOVA shows whether or not the means of the various

groups are significantly different from one another, as indicated by the F statistical

value. The F value shows whether two sample variances differ from each other or if

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they are from the same population. The F distribution is a probability distribution of

sample variances and the family of distributions changes with the changes in sample

size. In order words, the F value is the ratio of the variance between groups divided by

the variance within groups. Therefore, the greater the likelihood of between-group

variance compared with within-group variance, the greater the probability that the

means of the groups will be different (Sekaran et al., 2000).

In brief, One-way ANOVA was performed through two steps. In the first step

the significance of F value was determined. The F values were obtained from overall

ANOVA. The second step was the multiple comparisons between groups. However,

these comparisons were only applicable to those variables that were found to have a

significant difference in overall ANOVA; those variables with a significant F value.

In this section, the Scheffe test was used to compare the significant difference

between respondents’ academic background; STPM/Form Six, GCE A-Level, and

L.O.U. (comprising all other courses). The mean difference between groups indicated

whether groups were statistically significantly different from one another. In addition,

the Scheffe test was able to identify the strength of those differences. The results for

the F value and effect size for each variable are presented in Table 5.24; the

comparison between groups is shown in Table 5.25.

Table 5.24: One-way ANOVA, F values and effect size

Variable F P < .05 Cost of Education 22.31 Sig Degree (Content and Structure) 151.10 Sig Physical Aspects, Facilities and Resources 6.01 Sig Value of Education 49.93 Sig Institutional Information 2.01 NS People (Family, Friends, Peers and Teachers) 14.49 Sig Intention to Study 1.79 NS

* Note: Sig = Significant, NS = Not Significant

106

Table 5.25: One-way ANOVA, comparison between groups

Group

Variable

Respondent’s Qualification

(I)

Respondent’s Qualification

(J)

Mean Difference

(I-J) P < .05 Cost of Education STPM GCE A-Level 0.16 Sig STPM L.O.U. 0.29 Sig GCE A-Level L.O.U. 0.12 Sig

STPM GCE A-Level -0.82 Sig Degree (Content and Structure) STPM L.O.U. -0.54 Sig

GCE A-Level L.O.U. 0.29 Sig

STPM GCE A-Level -0.12 Sig Physical Aspects, Facilities and Resources STPM L.O.U. 0.01 NS GCE A-Level L.O.U. 0.13 Sig Value of Education STPM GCE A-Level -0.65 Sig STPM L.O.U. -0.23 Sig GCE A-Level L.O.U. 0.43 Sig Institutional Information STPM GCE A-Level -0.06 NS STPM L.O.U. 0.06 NS GCE A-Level L.O.U. 0.11 NS

STPM GCE A-Level -0.31 Sig People (Family, Friends, Peers and Teachers) STPM L.O.U. -0.41 Sig GCE A-Level L.O.U. -0.10 NS Intention to Study STPM GCE A-Level -0.01 NS STPM L.O.U. 0.09 NS GCE A-Level L.O.U. 0.10 NS

* Note: L.O.U. = Local Matriculation, Overseas Pre-U, University Foundation

Programme, Sig = Significant, NS = Not Significant

The results revealed that five out of seven variables are significantly different

among the respondent’s academic background. These variables are cost of education,

degree (content and structure), physical aspects, facilities and resources, value of

education, and people (family, friends, peers and teachers). The other two variables

remained insignificant. In terms of their effect size, degree (content and structure) and

value of education have a large effect size, followed by a moderate effect size for cost

107

of education and people (family, friends, peers and teachers). The variable which has

the significant smallest effect size is physical aspects, facilities and resources.

Further, from the results of group comparisons, students with STPM/Form six

backgrounds are more concerned with the cost of education than students with GCE

A-Level backgrounds and L.O.U.. Nevertheless, within the same variable, students

with GCE A-Level place a higher importance on the cost of education compared to

students with L.O.U. academic backgrounds. The detail of the comparison is

summarized in Table 5.26, and the further discussion is presented in Chapter 6.

Table 5.26: Findings from comparison of groups

Variable Significant Difference from Comparison of Groups

Cost of Education Students with STPM qualification place highest importance, followed by students with GCE A-Level, and students with L.O.U. qualifications

• STPM > GCE A-Level > L.O.U. .

Degree (Content and Structure) Students with GCE A-Level qualification place highest importance, followed by students with L.O.U. qualifications, and students with STPM qualification.

• GCE A-Level > L.O.U. > STPM

Physical Aspects, Facilities and Resources

Students with GCE A-Level qualification place higher importance than students with STPM and L.O.U. qualification. No significant difference found between students with STPM and L.O.U. qualification.

• GCE A-Level > STPM • GCE A-Level > L.O.U.

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Variable Significant Difference from

Comparison of Groups Value of Education Students with GCE A-Level qualification place

highest importance, followed by students with L.O.U. qualifications, and students with STPM qualification.

• GCE A-Level > L.O.U. > STPM

People (Family, Friends, Peers and Teachers)

Students with GCE A-Level and L.O.U. qualifications place higher importance than students with STPM qualification.

• GCE A-Level > STPM • L.O.U. > STPM

5.12 Conclusion of the Chapter

All the performed analyses were extensively discussed throughout this chapter.

Normality tests indicate that the sample is normally distributed. The factor analysis

and Cronbach’s alpha coefficient test confirm the validity and reliability of the

instrument employed in the present study. Correlation analysis and multiple linear

regression were carried out to establish the relationships between IVs and DV. Mean

Difference analyses were performed to identify the significant differences between the

respondent’s gender as well as academic background towards the importance placed

on a HEI. The further discussions of those findings are presented in Chapter 6.

CHAPTER 6

Discussion and Conclusion

6.1 Introduction

6.2 Discussion of Results

6.2.1 Normality Tests

6.2.2 Descriptive Analysis

6.2.3 Validity and Reliability Test

6.2.4 Pearson’s Correlation

6.2.5 Multiple Regression

6.2.6 Independent Sample t-Test

6.2.7 One-Way ANOVA

6.3 Conclusion

6.4 Implications

6.5 Recommendations

6.6 Contribution of the Study

6.7 Suggestion for Future Research

6.8 Conclusion of the Chapter

Chapter 1 Introduction

Chapter 2 Literature Review

Chapter 3 Conceptual Model

Chapter 4 Research Methodology

Chapter 5 Data Analysis and

Findings

Chapter 6 Discussion and

Conclusion

6.1 Introduction 6.2 Discussion of Results 6.3 Conclusion 6.4 Implications 6.5 Recommendations 6.5 Contribution of the Study 6.7 Suggestion for Future Research 6.8 Conclusion of the Chapter

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CHAPTER 6 DISCUSSION AND CONCLUSION

6.1 Introduction

This chapter presents in depth discussions on the findings obtained from Chapter 5.

The conclusion of the study discusses whether the findings support the proposed

hypotheses, answer the research questions, and achieve the research objectives.

Implications and recommendations are provided for HEI marketers to gain insights

into crafting their strategies for student recruitment. The contributions of the study are

discussed based on theoretical, methodological and practical approaches. Lastly,

suggestions for future research are presented in this chapter.

6.2 Discussion of Results

6.2.1 Normality Tests

According to the findings obtained from the analyses of sample normality, both

graphical and statistical results reflect the positive approach. Hence, the overall results

of the normality tests confirm that the sample used in this study is normally

distributed. This result reveals that the sample is well defined and the stratified

convenience sampling method is appropriate for the present study. Consequently, the

homoscedasticity of the sample is ensured and the sample is representative of the real

population. Thus, the findings of this study can be confidently generalized to the

population.

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6.2.2 Descriptive Analysis

Comparison of Means

In the descriptive analysis of the means of all items for each variable, all items

revealed mean scores of more than 3.00 (Table 5.5). Responses to the items were

measured on a five-point Likert scale where 1 means “Strongly Disagree” and 5

means “Strongly Agree”. Hence, the findings show that the majority of the

respondents agreed with the importance of the proposed items. Therefore, these items

are significant to their decision making when choosing a HEI to attend.

The means of all computed items variables are more than 3.00 (Table 5.6).

The results indicate that, in general, most of the respondents agreed with the

importance of all the proposed variables as influencing their study intention towards a

HEI. In the comparison of means between variables, “Physical aspects, facilities and

resources” has the highest mean score, followed by “institutional information”. “Cost

of education”, “Degree (content and structure)” and “People (family, friends, peers

and teachers)” have similar means, which are about 3.60. Subsequently, “value of

education” has the lowest mean score compared to the others.

The findings reveal that students place more importance on the HEI’s physical

aspects such as the location, conducive learning atmosphere, recreation and sports,

cleanliness, safe environment, campus social life, facilities, and quality faculty

members. In addition, students also place importance on the ability of the HEI to

provide relevant information. Information such as on-time application processes, area

of study of offered programmes, future job prospects and career opportunities, and

possibility of post-graduate studies upon the completion of the programme.

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Students consider the value of education as being relatively of less importance

to them. The reputation of the HEI, recommendations from academic institutions,

professional bodies, and industries are of less consequence to Malaysian students in

the selection of a HEI. This finding contrasts with the earlier study by Krishnan and

Nurtjahja (2007); a study of evaluative criteria for selection of PHEIs in Malaysia. In

their research, they found that private universities students placed highest importance

on the variable of “Recognition and reputation of the institution” (with a mean score

of 3.73).

This phenomenon can be explained by the different samples used in the

respective studies. Krishnan and Nurtjahja (2007) defined their targeted sample as

students who were studying in private universities and colleges. Whereas, the targeted

sample of the present study is tudents who are attending pre-university programmes.

Specifically, this group of students has not made their decision on the selection of a

HEI; they are potential customers of HEIs instead of existing students of HEIs.

Moreover, as discussed in Chapter 2, the nature of education is closely related

to service. According to Hoffman (2006) and Lovelock (2007), because of the four

basic service characteristics (intangibility, inseparability, heterogeneity and

perishability), an evaluation of a service can only take place when the service is

completely delivered, and the customer experiences the service instead of gaining

something from the service. Therefore, in the service industry, it is often found that

the customer perceives the value and importance of a service as different between the

before and after actual purchase. In other words, the perceived value of customers

alters over the service delivery process. In the previous study, students have chosen

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PHEIs as their study destination; however, students in the present study have not

decided to attend either a public HEI or PHEI. It shows that students in the previous

study were more focused on PHEIs. Thus, those students will have a distinct

perceived importance of the HEI they choose compared to the students in this study.

The findings of the previous study are in line with the findings obtained from

differential analysis of the students’ academic background in this study. The further

discussion is presented in section 6.2.7.

The dependent variable, “intention to study” has a high computed mean value

of 3.93, which is higher than all the independent variables. This finding indicates that

respondents have a high interest in pursuing their tertiary education. Their intention to

continue their studies at a HEI in the near future is assumed. In sum, based on the

computed mean value for each variable, the proposed six factors in this study affect

the students’ intention to study at a HEI.

Ranking Order of Important Factors

According to Table 5.10, Malaysian students place the cost of education, physical

aspects, facilities and resources of a HEI, and the influences from significant people

(family, friends, peers and teachers) as the first three most important criteria that

concerns them in their further study decision. As a matter of fact, results show that

Malaysian students have a significantly different perception of their intention to study

at a HEI compared to other nations. Joseph and Joseph (1998, 2000) have carried out

two similar studies of ranking order in two different cultural frameworks, namely,

New Zealand and Indonesia. The comparisons of ranking order of importance for

three distinct nations are shown in Table 6.1

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Table 6.1: Comparison of ranking order of importance for three distinct nations

Rank New Zealand, Year 1998 (N = 216)

Indonesia, Year 2000 (N = 110)

Malaysia, Year 2009 (N = 480)

1 Value of Education Course and Career Information**

Cost of Education

2 Degree (Content and Structure)

Physical Aspect, Facilities and Resources

Physical Aspects, Facilities and Resources

3 Cost of Education Cost of Education People (Family, Friends, Peers and Teachers)

4 Physical Aspect, Facilities and Resources

Degree (Content and Structure)

Degree (Content and Structure)

5 General* Value of Education Value of Education 6 N.A. N.A. Institutional Information Note: *Consists of institutional information and influences from significant people

(family, friends, peers and teachers)

**Includes influences from people (family, friends, peers and teachers)

N.A. = Not Applicable

The comparison shows that students from the different nations have distinctive

perceptions of the varying importance in their further study intention. Thus, HEI

marketing strategies will also vary from nation to nation. Some factors may be the

main focus in some countries while they may be of low significance in others.

Therefore, it is important to understand the psyche of students in the nation that

affects their intention to study at a particular HEI. In order words, there is no “one

size fits most” strategy for the education industry.

The perceived importance for Malaysian students is similar to Indonesian

students. The only difference is that “cost of education” ranked as the primary

concern for Malaysian students, whereas it was ranked number three by Indonesian

students. This is probably because Indonesia and Malaysia are located in the same

region. These two neighbouring countries often have similarities in their cultural

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frameworks. It is not surprising that students from both these countries share some

common perceived importance factors that influence their study intention

Comparatively, Malaysian students are assumed to be more cost conscious

than other nations. Students are willing to enrol in a HEI that provides education at a

reasonable cost. Furthermore, students are likely to prefer a HEI that provides them

with financial aid. Despite this, however, the physical aspect, facilities and resources

of a HEI was ranked as the second most important by both Malaysian and Indonesian

students. It may be concluded that ASEAN students prefer a HEI if they foresee that

the HEI has the ability to provide adequate facilities and resources for them.

Malaysian students’ study intention is influenced by a group of significant

people, such as family members, friends, peers, teachers, counsellors, relatives, etc.

This result is consistent with the findings from previous studies; personnel influence

on Asian students’ choice of HEI (McMahon, 1992; Mazzarol and Soutar, 2002;

Pimpa, 2003, Chen and Zimitat, 2006). Studies found that the influences from

significant personnel are more persuasive to Asian students, and that it does play an

important role in students’ choice of HEI in the Asian context.

According to Table 6.1, in comparison with New Zealand students, Malaysian

students show little concern for the content and structure of the degree, and the value

of the education. This fact is further supported by the outcome of an earlier study.

David and Anne (2007) cited that non-Malaysian students typically selected a HEI as

an aid to procuring a new identity. They found that this group of students viewed HE

with the hope of expunging provincial outlooks. These students wanted new ways of

viewing the world, new habits of thinking and new skills and approaches. As a result,

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New Zealand students placed greater importance on the value of education and the

degree (content and structure) obtained. They are much appreciative of the value and

the knowledge that can be gained from education. Thus, the appropriateness of the

reputation, organization, and content of degree is more significant to New Zealand

students compared to Malaysian students.

In summary, HEI authorities may use these findings regarding Malaysian

students perceived importance. In strategic planning, this finding may be useful in

managing the students’ priorities of the influencing factors. Ultimately, it helps to

achieve the goal of education that is beneficial to both HEIs and students.

6.2.3 Validity and Reliability Test

The validity and reliability of the instrument employed in this study were investigated

through factor analysis and Cronbach’s alpha coefficient test, respectively. The results

exhibit that a total of six IVs are identified from a pool of 36 items, and only one DV,

which consists of six items. Generally, IVs and the DV in this study have high

Cronbach’s alpha values, which are above 0.70, except the variable – “cost of

education” (0.65). Nevertheless, this variable is still considered as reliable as the

majority of the mean values of items within this variable fall within the optimal range

for the inter-item correlation of 0.20 to 0.40. In conclusion, the validity and reliability

test ensure the appropriateness of this instrument. The instrument is reliable and valid

in measuring the concepts proposed in this study. Moreover, it proves that the

adaption and further modification of the instrument are applicable in the present

study.

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6.2.4 Pearson’s Correlation

According to Table 5.21, the results reveal that all independent variables (IV1 to IV6)

are weak (<0.30) and positively correlated with the dependent variable at the high

significance level p <.01. Hence, there is a significant relationship between each

independent variable (IV1 to IV6) and the dependent variable.

6.2.5 Multiple Regression

Based on the findings obtained from the multiple linear regression analysis in

Chapter 5, the multiple regression equation is as follows:

DV = 2.18 + 0.18 IV1 + 0.19 IV2 + 0.11 IV6

Where,

DV = Intention to study at a HEI.

IV1 = Cost of Education

IV2 = Degree (Content and Structure)

IV6 = People (Family, Friends, Peers and Teachers)

There are three significant predictors presented in this model. Content and structure of

degree offered by a HEI has the highest coefficient value meaning that the content and

the structure of the degree has the highest contribution level towards students’

intention to study at a HEI. The second highest contribution predictor is cost of

education, followed by influence from significant people such as family members,

friends, peers and teachers. The remaining predictors are insignificant predictors in

the intention to study at a HEI. These silent predictors are physical aspects, facilities

and resources, value of education, and institutional information.

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This finding is almost in line with the ranking order of students’ perceived

importance. Students ranked cost of education, physical aspects, facilities and

resources, people (family, friends, peers and teachers) and degree (content and

structure) as the four most important factors in the decision making of choosing a

HEI. The only difference is that the physical aspects, facilities and resources is the

silent predictor in the multiple regression analysis.

Based on the regression equation, the constant value is 2.00, which is greater

than zero. This means that the respondents have a strong predisposition to further their

study even without the stimulus from proposed important factors. Furthermore, this

constant value is higher than all the coefficient values of the three predictors. To a

certain extent, these predictors may only act as some encouragement to motivate

students in choosing a particular HEI.

Taking into account the findings of the Pearson’s correlation and multiple

regression, the present study concludes that the proposed factors have a positive

relationship towards Malaysian students’ intention to study at a HEI. More

specifically, all the proposed factors appear to be important attributes in students’ HEI

selection. However, only three factors are the determinant attributes that distinguish

the intention to attend a particular HEI instead of others. For example, perhaps,

Malaysian students assume that if the HEI is able to offer certain programmes, the

HEI must have sufficient capabilities such as facilities, resources, and faculty

members to support the administration of those programmes. As a result, the physical

aspect of a HEI may not be a key attribute that students see as a significant difference

among competing alternatives.

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In summary, there are three key determinant attributes that affect students’

intention to study at a HEI. These attributes are cost of education, content and

structure of the degree, and influences from significant people such as family

members, friends, peers and teachers. Thus, the proposed hypothesis (H7) is rejected

due to some proposed predictors being insignificant in the multiple regression

analysis.

In conclusion, based on the results of the multiple regression, the first, second

and sixth hypothesis (H1, H2 and H6) are accepted, whereas the third, fourth and fifth

hypothesis (H3, H4 and H5) are rejected.

6.2.6 Independent Sample t-test

According to Table 5.25, four out of seven proposed variables are significantly

different between the gender of the respondents. These variables are cost of education,

physical aspects, facilities and resources, value of education, and intention to study.

The other three variables – degree (content and structure), institutional information,

and people (family, friends, peers, and teachers) are not significantly different

between male and female students.

Generally, the mean difference shows that female students are more concerned

with these three important attributes than male students. Also, the findings reveal that

female students have a higher intention to further their study at a HEI than male

students. This result is consistent with earlier studies regarding the gender differences

in shopping behaviour (Meyers-Levy et al., 1991; Mansfield and Warwick, 2005).

Those studies indicated that females attempt to engage in effortful, itemized analysis

of all available information giving equal weight to information of attributes relevant

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to self and others; whereas, males tend to rely on a single cue or a cue that is highly

available and particularly salient in the focal context. Hence, this could help explain

why female students take more consideration on these important attributes than male

students in the HEI context. Furthermore, the findings indicate that Malaysian female

students often engage in comprehensive processing of information, and exhaustive

evaluation of important attributes. Consequently, HEI marketers may take this finding

into consideration for designing and managing integrated marketing communications

(IMC) for potential students, especially female students.

6.2.7 One-Way ANOVA

According to Table 5.24, the results reveal that five out of seven variables are

significantly different between respondent’s academic backgrounds. These variables

are cost of education, degree (content and structure), physical aspects, facilities and

resources, value of education, and people (family, friends, peers and teachers). The

other two variables are not significantly different between students’ academic

backgrounds.

In the variable of cost of study, students with a STPM background present

higher mean values compared to students with A-levels and other academic

backgrounds. This shows that STPM students are more concerned with financial

consumption during their study compared to others. In addition, students with an A-

level background also have a higher mean value than students with other academic

backgrounds.

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It is apparent that students with an A-level background view the content and

structure of the degree offered by a HEI as typical compared to students with the other

two different academic backgrounds. This finding indicates that A-level students are

more conscious of the availability and suitability of the offered courses by a HEI.

Moreover, students with other backgrounds also have a higher mean value than

students with STPM backgrounds.

In the variable of physical aspects, facilities and resources, students with A-

level background reveal a significantly higher mean value compared to students with

STPM and other academic backgrounds. This result indicates that A-level students

consider the facilities and physical aspects that a HEI could offer them as important.

Nonetheless, there is no significant difference between STPM students and other

academic background students in the perceived importance of a HEIs physical

aspects.

Furthermore, students with A-level background view the value of education as

more important compared to students from the other two academic backgrounds. This

output indicates that A-level students are more appreciative of the importance and

principles of quality education. Additionally, students with other backgrounds also

have a higher mean value than students with STPM backgrounds.

In conclusion, male and female students, and students with different academic

background place significantly different importance on the factors that influence

students’ intention to study at a higher educational institution. Hence, there is

sufficient evidence supporting the two hypotheses (H7 and H8). Thus, these

hypotheses are accepted in this study. The discussion of differential analyses is

summarized in Table 6. 2.

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Table 6.2: Summary of findings from differential analyses

Difference Variable Gender Academic Background

Cost of Education Female students are more cost conscious than male students

STPM students place highest importance, followed by A-level, and L.O.U., as follows: • STPM > GCE A-Level > L.O.U.

Degree (Content and Structure)

No significant difference between male and female students

A-level students place highest importance, followed by L.O.U., and STPM, as follows: • GCE A-Level > L.O.U. > STPM

Physical Aspects, Facilities and Resources

Female students are more concerned than male students

A-level students place more importance than STPM and L.O.U.. No significant difference between STPM and L.O.U.. As follows: • GCE A-Level > STPM • GCE A-Level > L.O.U.

Value of Education Female students

appreciate the value more than male students

A-level students place highest importance, followed by L.O.U., and STPM, as follows: • GCE A-Level > L.O.U. > STPM

Institutional Information No significant

difference between male and female students

No Significant difference between students from different academic background

People (Family, Friends, Peers and Teachers)

No significant difference between male and female students

A-level and L.O.U. students place more importance than STPM students. No significant difference between A-level and L.O.U.. As follows: • GCE A-Level > STPM • L.O.U. > STPM

Intention to Study Female students have

higher intention than males

No Significant difference between students from different academic background

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6.3 Conclusion

According to the findings from the inferential analyses, all proposed IVs are

significant and positively correlated to the DV. Therefore, the first to sixth proposed

hypotheses (H1 to H6) in this study are accepted. In addition, the eighth and ninth

proposed hypotheses (H7 and H8) are also accepted. This statement is supported by

the findings of the present study that reveal a significant difference between students’

gender and academic backgrounds on their perceived important factors for selecting a

HEI. The overall result of the hypotheses testing is presented in Table 6.3.

To answer the first research question (Q1), the significant factors influencing

students’ intention to study at a HEI are cost of education, degree (content and

structure), and people (family, friends, peers, and teachers). The factor of degree

(content and structure) has the highest impact on students’ intention to study at a HEI,

followed by cost of study, and people (family, friends, peers, and teachers).

To answer the second research question (Q2), male and female students do

differ significantly in the selection criteria that they consider important when

choosing a HEI. Male and female students significantly differ in the following factors:

cost of education, physical aspects, facilities and resources, and value of education. In

general, female students place higher weight on these important factors. Additionally,

female students reveal that they have a higher study intention than male students.

Also, students from different academic backgrounds such as STPM, GCE A-level,

and other academic backgrounds significantly differ in the selection criteria they

consider important when choosing a HEI. These factors are cost of education, degree

(content and structure), physical aspects, facilities and resources, value of education,

and people (family, friends, peers and teachers). Generally, students from different

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academic backgrounds tend to have distinctive opinions concerning the important

factors affecting their choice of HEI.

In conclusion, the present study is successful in testing the proposed

hypotheses. Moreover, the research questions are answered as well as achieving the

objectives of this study. In other words, this study is complete, and the findings of the

study could be beneficial to both students (customers), and institutions (service

providers).

Table 6.3: Overall result of hypotheses testing

Hypothesis Result H1 The cost of education is a significant factor that influences

students’ intention to study at a HEI

Accepted

H2 The content and structure of degree is a significant factor that influences students’ intention to study at a HEI

Accepted

H3 The physical aspects, facilities and resources of an institution are a significant factor that influences students’ intention to study at a HEI

Rejected

H4 The value of education is a significant factor that influences students’ intention to study at a HEI

Rejected

H5 The institutional information is a significant factor that influences students’ intention to study at a HEI

Rejected

H6 The significant people (family, friends, peers and teachers) is a significant factor that influences students’ intention to study at a HEI

Accepted

H7 Male and female students will differ in the importance placed on the factors that influence students’ intention to study at a higher educational institution.

Accepted

H8 Students with different academic background will differ in the importance placed on the factors that influence students’ intention to study at a higher educational institution.

Accepted

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6.4 Implications

Through this study, Malaysian students have shown the proposed variables that

influence their intention to study at a HEI. As a result, it will be interesting to further

investigate the impact of those variables on their study intention. Moreover, it may

create a complete picture if the differences among students’ gender and academic

backgrounds were defined. Therefore, findings from the analyses in this study are

integrated in order to provide appropriate, meaningful, and comprehensive

implications to HEI marketers as well as other researchers. The overall implications

of this study are presented in Table 6.4.

According to Table 6.4, there are six important factors that influence students

in their HEI choice. In essence, it is suggested that HEI marketers focus more

attention on the determinant factors such as cost of education, influences from

significant people (family members, friends, peers and teachers), and content and

structure of degree. Although all factors influence students’ HEI choice, to a certain

extent, these significant factors are the key factors influencing their decision to attend

a HEI. In order words, HEIs may develop their institutional positioning, and craft

relevant strategies based on the findings accordingly.

It will enable HEIs to gain certain insights and develop a competitive

advantage over competitors. In fact, knowing the actual reason that students choose a

HEI is the essential element that allows a HEI to be sustainable and survive in an

increasingly competitive HE environment.

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Table 6.4: Overall implication of findings from the present study

Difference Rank Variable

Relationship with study intention Impact Gender Academic Background

1 Cost of Education

Positive Significant factor

Female students are more cost conscious than male students

STPM students place highest importance, followed by A-level, and L.O.U., as follows: • STPM > GCE A-Level > L.O.U.

2 Physical Aspects, Facilities and Resources

Positive Insignificant factor

Female students are more concerned than male students

A-level students place more importance than STPM and L.O.U. students. No significant difference between STPM and L.O.U. students. As follows: • GCE A-Level > STPM • GCE A-Level > L.O.U.

3 People (Family, Friends, Peers and Teachers)

Positive Significant factor

No significant difference between male and female students

A-level and L.O.U. students place more importance than STPM students. No significant difference between A-level and L.O.U. students. As follows: • GCE A-Level > STPM • L.O.U. > STPM

4 Degree (Content and Structure)

Positive Significant factor

No significant difference between male and female students

A-level students place highest importance, followed by L.O.U., and STPM, as follows: • GCE A-Level > L.O.U. > STPM

5 Value of Education

Positive Insignificant factor

Female students appreciate the value more than male students

A-level students place highest importance, followed by L.O.U., and STPM, as follows: • GCE A-Level > L.O.U. > STPM

6 Institutional Information

Positive Insignificant factor

No significant difference between male and female students

No Significant difference between students from different academic background

N.A. Intention to Study

N.A. N.A. Female students have higher intention than male students

No Significant difference between students from different academic background

Note: N.A. = Not Applicable

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Furthermore, such findings assist marketers to plan and improve their

marketing strategy for recruiting students. It may aid HEIs in Malaysia to retain

Malaysian students and deter them from studying abroad. In addition, there is also a

strong possibility of attracting foreign students to study in Malaysia. Thus, by doing

this, Malaysia is able to reverse the outflow of funds and reduce the current service

deficit. In order to achieve this goal, HEI authorities must understand the students’

needs and the HEI selection criteria.

6.5 Recommendations

HE is a services industry and within this industry HEIs play a role as service

providers with students as the customers. The decision made to study at a particular

HEI is often referred to as a high purchase involvement. It is because the decision

involves many people surrounding the student, and such decisions are normally

associated with a higher perceived risk. Therefore, usually many attributes are taken

into consideration by students in evaluating the HEI before a decision is made.

According to the findings presented in this study, both the significant and

insignificant factors are identified. Further, differences among students’ gender and

academic background concerning these attributes are clearly defined. As a result, HEI

authorities may make use of these findings to tailor their marketing elements with

potential students’ needs. For instance, in this study students with STPM background

are more sensitive to expenditure; HEIs could offer those students scholarships or

other financial aid to reduce their perceived risk in selecting the HEI of their choice.

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6.6 Contribution of the Study

Theoretical

The findings of this study prove that male and female students differ in the selection

criteria that they consider important when choosing a HEI in the Malaysian context.

This approach is in line with the theory proposed in previous studies (Shank and

Beasley, 1998; Mansfield and Warwick, 2005). Furthermore, the findings reveal that

students from different academic backgrounds differ in their perceived importance

towards a HEI. This approach confirms that the assumption in a previous study by

Elizabeth Ng (2003) is demonstrable. In her study, she found that Malaysian students

from different courses at pre-university level have distinct selection criteria in

selecting educational institutions abroad.

Methodological

The research instrument employed in this study is based on the adaption and further

modification of previous studies (Cubillo et al., 2006; Joseph and Joseph, 1998; 2000;

Zeithaml et al., 1996). This instrument has passed the validity and reliability tests in

this study indicating that the adaption and modification of this instrument are

appropriate. In other words, this is a new approach instrument, and is applicable in the

Malaysian context.

Practical

The findings of this study can assist HEI authorities to have a better understanding

regarding the factors that influence students’ intention to study at a HEI. This study

discusses the difference between students’ gender and academic background

concerning the important attributes. It enables HEI authorities to have a fuller

comprehension of students’ needs.

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6.7 Suggestion for Future Research

Further research is suggested to investigate some other underlying concepts, as

follows:

1. To identify gender difference in parents’ evaluative criteria when

students are in the process of selecting a college. Mansfield and

Warwick (2006) carried out a study that addressed differences by parent

gender with regards to the HEI selection process in the United States.

They found that male and female parents differ in the selection criteria

and that it directly affects the students’ ultimate choice of HEI. In fact,

the majority of Malaysian students studying in HEIs do so at the cost of

their parents. It will be interesting to see whether such differences also

arise in the Malaysian context.

2. In this study, the dependent variable: students’ intention to study did not

specify whether the intention was to further their studies at a public or

private HEI. As a matter of fact, students’ perceived values of public

HEIs and PHEIs are very different. Krishman and Nurtjahja (2007) cited

that PHEIs charge students a higher fee than public HEIs. Hence, the

students’ evaluative criteria for a PHEI will be very different from that

of a public HEI. Consequently, future research may be redesigned to

include two parallel sets of questionnaires to measure the two distinct

variables, namely, the intention to study at a public HEI and the intention

to study at a PHEI.

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3. To identify the differences among students’ socioeconomic factors

concerning their intention to study at a HEI, future studies could

compare the differences between students’ socioeconomic factors, such

as ethnicity and family income, which may affect their intention to study

at a HEI.

6.8 Conclusion of the Chapter

The findings of the present study are extensively discussed in this chapter. Moreover,

this chapter summarises the tasks completed in the present study by reporting the

hypotheses testing, answering the research questions, and describing the achievement

of the research objectives. Additionally, this chapter outlines some implications and

recommendations for HEI authorities for gaining a better understanding of students’

needs. Finally, the chapter describes the contributions of the study, and then proposes

some insights for future research.

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References Abrahmson, T. and Hossler, D. (1990), “Applying Marketing Strategies in Student

Recruitment”, The Strategic Management of College Enrollments. San Francisco: Jossey Bass.

Ahmed, Z.U., Johnson, J.P., Ling, C.P., Fang, T.W. and Hui, A.K. (2002), “Country-of-origin

and Brand Effect on Consumers’ Evaluations of Cruise Lines”, International Marketing Review, Vol. 19, No. 2/3, pp. 279-302.

Alexander, K.L. and Eckland, B.K. (1975), “Basic Attainment Processes: A Replication and

Extension”, Sociology of Education, Vol. 48, pp. 457-495. Armstrong, J.J. and Lumsden, D.B. (1999), “Impact of Universities’ Promotional Materials

on College Choice”, Journal of Marketing for Higher Education, Vol. 9, No. 2, pp. 83-91.

Anderson, E. and Sullivan, M. (1993), “The antecedents and consequences of customer

satisfaction for firms”, Marketing Science, Vol. 12, pp. 125-43. Annie Wong, M.N. and Hamali, J. (2006), “Higher Education and Employment in Malaysia”,

International Journal of Business and Society, Vol. 7, No. 1, pp. 102-118. Baird, L. (1967), The Educational Tools of College Bound Youth, American College Testing

Program Research Report, Iowa. Bakan, D. (1966), The Duality of Human Existence: An Essay on Psychology and Religion,

Chicago. IL: Rand McNally Publishing Company. Bartlett, M.S. (1954), “A Note on the Multiplying Factors for Various Chi Square

Approximations”, Journal of the Royal Statistical Society, Vol. 16, pp. 296-298. Bean, J.P. (1990), “Why Students Leave: Insights from Research’, The Strategic

Management of Enrollment, San Francisco: Jossey-Bass. Becker, G.S. (1975), Human Capital: A Theoretical and Empirical Analysis with Special

Reference to Education, New York Bureau of Economic Research, Columbia University. Bennet, D. (2006), “The Effectiveness of Current Student Ambassadors in HE

Marketing Recruitment and Retention”, Paper Presented at the International Conference on HE marketing Cyprus, 3-5 January.

Binsardi, A. and Ekwulugo, F. (2003), “International Marketing of British Education: Research

on the Students' Perception and the UK Market Penetration”, Marketing Intelligence & Planning, Vol. 21 No. 5, pp. 318-327.

Briggs, S.R. and Cheek, J.M. (1986), “The Role of Factor analysis in the Development and

Evaluation of Personality Scales”, Journal of Personality, Vol. 54, pp. 106-148.

131

Bingham, F. (1989), “Promotion: An Inseparable Part of the Marketing Effort”, Journal of Marketing for Higher Education, Vol. 1, No. 2, pp. 15-26.

Borjas, G.J. (1994), “The Economics of Immigration”, Journal of Economic Literature,

December, pp. 16-67 Bowers, T. and Pugh, R. (1972), A Comparison of Factors Underlying College Choice by

Students and Parents, American Educational Research Association Annual Meeting. Brennan, L. (2001). How Prospective Students Choose Universities: A Buyer Behavior

Perspective. Unpublished Doctoral dissertation, University of Melbourne, Australia. Brookes, M. (2003), “Higher Education: Marketing in a Quasi-commercial Service Industry”,

International Journal of Non-profit and Voluntary Sector Marketing, Vol. 8 No. 2, pp. 1465-520.

Bourke, A. (2000), “A Model of the Determinants of International Trade in Higher

Education”, The Service Industries Journal, Vol. 20, No. 1, pp. 110-38. Cabera, A.F., La Nasa, S.M. (2000), Understanding the College-Choice Process New

Directions for Institutional Research, No. 107 San Francisco: Jossey Bass. Cabera, A.F., Nora, A. and Castaneda, M.B. (1992), “The Role of Finances in the Persistence

Process: A Structural Model”, Research in Higher Education, Vol. 33, No. 5, pp. 571-593.

Carpenter, P., and Fleishman, J. (1987), “Linking intentions and behavior: Australian

students’ college plans and college attendance”, American Educational Research Journal, Vol. 24, pp.79-105.

Carver, R.H., Nash, J.G. (2006), Doing Data Analysis with SPSS Version 14, Thomson Book

Corporation, Canada. Cavana, R.Y., Delahaye, B.L. and Sekaran, U. (2000), Applied Business Research:

Qualitative and Quantitative Methods, John Wiley & Sons Australia, Ltd., Singapore. Chapman, D. (1981), “A Model of Student College Choice”, Journal of Higher Education,

Vol. 52, pp. 490-505. Chapman, R. (1979), “Pricing Policy and the College Choice Process”, Research in Higher

Education, Vol. 10, No. 37, p. 57. Chapman, R. (1986), “Towards a Theory of College Selection: A Model of College Search

and Choice Behaviour”, Advances in Consumer Research, Vol. 13, Association for Consumer Research, Provo, Utah.

Chen, C.H. and Zimitat, C. (2006), „Understanding Taiwanese Students’ Decision-Making

Factors Regarding Australian International Higher Education“, The International Journal of Educational Management, Vol. 20, No. 2, pp. 91-100.

132

Choy, S.P. and Ottinger, C. (1998), Choosing a Postsecondary Institution. Statistical Analysis Report. Washington, DC: National Center for Education Statistics.

Cleopatra, V., John, W.L. and Robert, A.P. (2004), “University Selection: Information

Requirements and Importance”, The International Journal of Educational Management, Vol. 18, No. 3, pp 160-171.

Coccari, R. and javalgi, R. (1995), “Analysis of Students’ Needs in Selecting A College or University in a Changing Environment”, Journal of Marketing for Higher Education, Vol. 6, No. 2, pp. 27-39.

Cohen, J.W. (1988), Statistical Power Analysis for the Behavioural Sciences, 2nd Edition,

Hillsdale, NJ: Lawrence Erlbaum Associates. Coleman, J. (1966). Peer Culture and Education in Modern Society, College Peer Groups:

Problems and Prospects for Research. Chicago: Aldine. Connor, H. (2001), “Deciding for or Against Participation on Higher Education: The View of

Young People from Lower Social Class Backgrounds”, Higher Education Quarterly, Vol. 55, No. 2, pp. 204-224.

Cook, R. and Zallocco, R. (1983), “Predicting University Preference and Attendance”,

Research in Higher Education, Vol. 19 No. 2, pp. 197- 211. Cronin, J. and Taylor, S. (1992), " Measuring Service Quality: A Re-examination and

Extension", Journal of Marketing, Vol. 56, July, pp. 55-68. Cubillo, J.M., Sanchez, J., Cervino, J. (2006), “International Students’ Decision-making

Process”, The International Journal of Educational Management, Vol. 20 No. 2, pp. 101-115.

Dawidow, W.H. and Uttal, B. (1989), “Service Companies: Fows or Faller”, Harvard

Business Review, Vol. 67, July-August, pp.77. Dehne, G., Brodigan, D. and Topping, P. (1991), Marketing Higher Education: A Handbook

for College Administrators, Washington, DC: Consortium for the Advancement of Private Higher Education.

DeVellis, R.F. (2003), Scale Development: Theory and Applications, 2nd Edition, Thousand

Oaks, California: Sage. Discenza, R., Ferguson, J. and Wisner, R. (1985), “Marketing Higher Education: Using A

Situation Analysis to Identify Prospective Student Needs in Today's Competitive Environment”, NASPA, Vol. 22, pp. 18-25.

Donald, R.C. and Pamela, S.C. (2003), Business Research Methods, McGraw-Hill Inc.,

United State. Elizabeth Ng P.P. (2003), “Factor Affecting Students When Selecting Education Institutions

Abroad”, unpublished MBA Dissertation, University Putra Malaysia, Malaysia.

133

Ennew, C., Reed, G. and Binks, M. (1993), “Importance-performance Analysis and the Measurement of Service Quality,” European Journal of Marketing, Vol. 27 No. 2, pp. 59-70.

Falsey, B. and Haynes, B. (1984), “The College Cannel: Private and Public Schools

Reconsidered”, Sociology of Higher Education, Vol. 57, pp. 111-122. Fischer, E. and Arnold, S. (1994), “Sex, Gender Identity, Gender Role Attitudes, and Consumer

Behaviour”, Psychology & Marketing, Vol. 11, No. 2, pp. 163-182. Flint, T. A. (1993), “Early Awareness of College Financial Aid: Does it Expand College Choice

?”, Review of Higher Education, Vol. 16, No. 3, pp. 309-327. Flint, T. A. (1992), “Parental and Planning Influences on the Formation of Student College Choice

Sets”, Research in Higher Education, Vol. 33, No. 3, pp. 689-708. Ford, J., Joseph, M. and Joseph, B. (1998), “An Importance Performance Analysis of Service

Quality in Education: A Comparison of New Zealand and United States Business Students”, The Journal of Services Marketing, Vol. 7, No. 6, pp. 156-158.

Fornell, C. (1992), “A National Customer Satisfaction Barometer: The Swedish Experience”,

Journal of Marketing, Vol. 56, January, pp. 6-21. Foskett, N. and Hemsley-Brown, J. (2001), Choosing Futures: Young Peoples Decision

Making Bin Education Training and Career Markets, Routledge Falmer, London. Foskett, N. (1999), “Strategy, External Relations and Marketing”, Managing External

Relations in Schools and Colleges, Paul Chapman, London. Foskett, N., Maringe, F. and Roberts, D. (2006), Changing Fee Regimes and Their Impact on

Student Attitudes to Higher Education, Higher Education Academy UK, Vol. 22, No. 2, pp 23-31.

Freeman, K. (1997), “Increasing African Americans’ Participation in Higher Education:

African American students’ Perspective”, Journal of Higher Education, Vol. 68, No.5, pp. 523-550.

Gibbs, P. (2002), “From the Invisible Hand to the Invisible Hand-Shake: Marketing Higher

Education’, Research in Post Compulsory Education, Vol. 7, No. 3, pp. 325-338. Gray, B.J., Fam, K.S. and Llanes V.A. (2003), “Branding Universities in Asian Markets”,

Journal of Product and Brand Management, Vol. 12, No. 2, pp. 108-120. Green, R.J. and Hill, J.H. (2003), “Sex and Higher Education: Do Men and Women Attend

College for Different Reasons ?”, College Student Journal, Vol. 12, pp 1-10. Gutman, J. and Miaoulis, G. (2003), “Communicating a Quality Position in Service Delivery:

An Application in Higher Education”, Managing Service Quality, Vol. 13 No. 2, pp. 105-11.

134

Hall, R. (1993), “A Framework Linking Intangible Resources: An Capabilities to Sustainable Competitive Advantage”, Strategic Management Journal, Vol. 14, pp. 607-618.

Harvey, J.A. and Busher, H. (1996), “Marketing Schools and Consumer Choice”,

International Journal of Educational Management, Vol. 10 No. 4, pp. 26-32. Hassan, A. (2006), “Current Practices of Malaysia Higher Education”, International forum:

“Globalization and Integration in Higher Education”, Kolej Univarsiti Sains dan Tecknologi Malaysia, Malaysia.

Hassan, F.H. and Sheriff, N.M. (2006), “Students’ Need Recognition for Higher Education at

Private Colleges in Malaysia: An Exploratory Perspective”, Sunway Academic Journal, Vol. 3, pp. 61-71.

Hawes, J.M. and Rao, C.P. (1985), “Using Importance-performance Analysis to Develop

Health Care Marketing Strategies”, Journal of Health Care Marketing, Vol. 5 No. 4, pp. 19-25.

Hawes, J.M., Kiser, G.E. and Rao, C.P. (1982), “Analyzing the Market for Planned

Retirement Communities in the Southwest”, Baylor Business Studies, Vol. 13, August-September-October, pp. 39-46.

Hayden, M. (2000), “College Choice Influences: Urban High School Students Respond.

Community College”, Journal of Research and Practice, Vol. 24, pp. 487-494. Hayes, T.J. (1989),”How Students choose a College: A Qualitative Approach”, Journal of

Marketing for Higher Education, Vol. 2, No. 1, pp. 19-27. Hayes, T.J., Walker, M. and Trebbi, G. (1995), “Promoting to Women: It’s Not What You

Think” in Symposium for Marketing of Higher Education, Chicago:American Marketing Association.

Hemmasi, M., Strong, K. and Taylor, S. (1994), “Measuring Service Quality for Strategic

Planning and Analysis in Service Firms”, Journal of Applied Business Research, Vol. 10 No. 4, pp. 24- 34.

Hemsley-Brown, J. (1999), “College choice: Perceptions and Priorities”, Educational

Management & Administration, Vol. 27 No. 1, pp. 85-98. Hemsley-Brown, J. and Oplatka, I. (2006), “Universities in A Competitive Global

Marketplace: A Systematic Review of the Literature on Higher Education Marketing, International Journal of Public Sector Management, Vol. 19, No. 4, pp. 316-338.

Hossler, D. (1985), A Research Overview of Student College Choice, Association for the

Study of Higher Education, Chicago, IL. Hossler, D. (1999), Effective Admissions Recruitment. New Directions for Higher Education.

Jossey- Bass.

135

Hossler, D., Bean, J.P. and Associates (1990). The Strategic Management of College Enrollments. San Francisco: Jossey-Bass.

Hossler, D., Braxton, J.M. and Coopersmith, G. (1989). “Understanding student college

choice”, in Smart, J.C. (ed.), Higher Education: Handbook of Theory and Research. New York: Agathon Press.

Hossler, D. and Gallagher, K.S. (1987), “Studying Student College Choice: A Three-Phase

Model and the Implications for Policymakers”, College and University, Vol. 62, No. 3, pp. 207-22.

Hossler, D., Hu, S., Schmit, J. (1998). Predicting Student Sensitivity to Tuition and Financial

Aid, Paper presented at the annual meeting of American Educational Research Association, San Diego California

Hossler, Don., Schmit, Jack., & Vesper, Nick., (1999), Going to College, How Social,

Economic, and Educational Factors Influence the Decisions Students Make, The John Hopkins University Press, Baltimore & London.

Hooley, G.J. and Lynch, J.E. (1981) “Modeling the Student University Choice Process

Through the Use of Conjoint Measurement Techniques”, European Research, Vol. 9 No. 4, pp. 158-70.

Houston, M. (1979), “Cognitive Structure and Information Search Patterns of Prospective

Graduate Business Students”, Advances in Consumer Research, Vol. VII, October, pp. 552-7.

Ivy, J.P. (2001), “University Image: The Role of Marketing in MBA Student Recruitment in

State Subsidized Universities in the Republic of South Africa”, Unpublished Doctoral dissertation, University of Leicester, Leicester.

Ivy, J.P. (2001), “Higher Education Institution Image: A Correspondence Analysis

Approach”, The International Journal of Educational Management, Vol. 15, No. 6/7, pp. 276-282.

Jackson, G. A., (1982), “Public Efficiency and Private Choice in Higher Education”,

Educational Evaluation and Policy Analysis, Vol. 4, No. 2, pp. 237-247. Jacobs, J. (1999), “Gender and the Stratification of Colleges”, The Journal of Higher

Education, Vol. 70, No. 2, pp. 161-187. James, J., Baldwin, G. and McInnis, C. (1999), “Which University ? The Factors Influencing

the Choice of Prospective Undergraduates. A study undertaken under the Australian Higher Education Division’s Evaluations and Investigation Programme, Canberra.

John, E.P. (1990), “Price Response in Enrollment Decisions: An Analysis of the High School

and Beyond Sophomore Cohort”, Research in Higher Education, Vol. 31, No. 2, pp. 161-176.

136

Joseph, M. and Joseph, B. (1998), “Identifying Need of Potential Students in Tertiary Education for Strategy Development”, Quality Assurance in Education, Vol. 6, No. 2, pp. 90-96.

Joseph, M. and Joseph, B. (2000), “Indonesian Students’ Perceptions of Choice Criteria in the

Selection of a Tertiary Institution: Strategic Implications”, The International Journal of Educational Management, Vol. 14, No. 1, pp. 40-44.

Joseph, M. and Joseph, B. (1997), “Service Quality in Education: The Role of Student as

Primary Consumer”, Quality Assurance in Education, Vol. 5, No. 1, pp. 15-21. Kaiser, H. (1970), “A Second Generation Little Jiffy”, Psychometrika, Vol. 35, pp. 401-415. Kaiser, H. (1974), “An Index of Factorial Simplicity”, Psychometrika, Vol. 39, pp. 31-36. Kinnell, M. (1989), “International Marketing in UK Higher Education: Some Issues in

Relation to Marketing Educational Programmes to Overseas Students”, European Journal of Marketing, Vol. 23 No. 5, pp. 7-21

Kinnell, M. and MacDougall, J. (1997), Marketing in the Non-For-Profit Sector. Jordan Hill,

Oxford: Butterworth-Heinemann. Kotler, P. (1975), Marketing for Nonprofit Organization, Englewood Cliffs, NJ: Prentice-

Hall Inc. Kotler, P. (1979), “Strategies for Introducing Marketing into Nonprofit Organizations”,

Journal of Marketing, Vol. 43, no. 1, pp. 37-44. Kotler, P. and Andreasen, A.R. (1996), Strategic Marketing into Nonprofit Organizations, 5th

Edition, Upper Saddle River, NJ: Prentice-Hall Inc. Kotler, P. and Fox, K.F.A. (1985), Strategic Management for Educational Institutions,

Prentice-Hall, Upper Saddle River, NJ. Kotler, P. and Fox, K.F.A. (1995), Strategic Management for Educational Institutions, 2nd

Edition, Prentice-Hall, Upper Saddle River, NJ. Kotler, P. and Levy, S.J. (1969), “Broadening the Concept of Marketing”, Journal of

Marketing, Vol. 33, No. 1, pp. 10-15. Krampf, R.F. and Heinlein, A.C. (1981), “Developing Marketing Strategies and Tactics in

Higher Education Through Target Market Research”, Decision Sciences, Vol. 12 No. 2, pp. 175-193.

Krishnan, A. and Nurtjahja, O. (2007), “Evaluative Criteria for Selection of Private

Universities and Colleges in Malaysia”, Journal of International Management Studies, Vol. 2, No. 1, pp 22-31.

Krone, F., Gilly, M., Zeithaml, V. and Lamb, C. (1983), “Factors Influencing the Graduate

Business School Decision”, American Marketing Association Educators’ Proceedings, Chicago, IL.

137

Laroche, M., Saad, G., Cleveland, M. and Browne, E. (2000), “Gender Differences in

Information Search Strategies for a Christmas Gift”, Journal of Consumer Marketing, Vol. 17, No. 6, pp. 500-524.

Leslie, L. L., and Brinkman, P. T. (1988), The Economic Value of Higher Education.

American Council on Education, Macmillan. Leslie, L. L., Johnson, G. P. and Carlson, J. (1977), “The Impact of Need-Based Student Air

upon the College Attendance Decision”, Journal of Education Finance, Vol. 2, No. 3, pp. 269-285.

Levitt, T. (1980), “Marketing Success Through Differentiation of Anything”, Harvard

Business Review, February, pp. 83-89. Lewis, G.H. and Morrison, S. (1975), A Longitudinal Study of College Selection. Technical

Report No. 2, Pittsburgh, PA: Carnegie Mellon University. Lin, L. (1997), “What are Student Education and Educational Related Needs ?”, Marketing

and Research Today, Vol. 25, No. 3, pp. 199-212. Lin, C. and Kao, D.T. (2004), “The Impact of Country-of-origin on Brand Equity”, Journal

of American Academy of Business, Vol. 5, No. 1/2, pp. 37-40. Litten, L. (1980), “Marketing Higher Education”, Journal of Higher Education, Vol. 51, No.

4, pp. 40-59. Litten, L.H. (1982), “Different Strokes in the Applicant pool: Some Refinements in a Model

of Students Choice”, Journal of Higher Education, Vol. 4, pp.383-402. Loudon, D. and Della Bitta, A. (1988), Consumer Behaviour: Concepts and Applications, 3rd

edition, McGraw-Hill International, Singapore. Lovelock, C. (2007), Services Marketing: People, Technology, Strategy, 6th edition,

Prentice-Hall Inc, Englewood Cliffs, NJ. Maehl, W. (2000), The Challenge to Postsecondary Education From An Expanding Pool of

Learners, Lifelong Learning at Its Best: Innovative Practice in Adult Credit Programs, San Francisco, CA: Jossey-Bass Publishers.

Maguire, J. and Lay, R. (1981), “Modeling the College Choice: Image and Decision”,

College and University, Vol. 56, pp. 113-26. Manilla, J. and James, J. (1977), “Importance-performance analysis”, Journal of Marketing,

Vol. 41, January, pp. 77-9. Mansfield, P.M. and Warwick, J. (2005), “Gender Differences in Students’ and Parents’

Evaluative Criteria When Selecting a College”, Journal of Marketing for Higher Education, Vol. 15, No. 2, pp. 47-80.

138

Maringe, F. (2006), “University and Course Choice: Implications for Positioning,

Recruitment and Marketing”, The International Journal of Educational Management, Vol. 20, No. 6, pp 466-479.

Mazzarol, T. and Hosie, P. (1996), “Exporting Australian Higher Education: Future

Strategies in maturing market”, Quality Assurance in Education, Vol. 4, No. 4, pp. 37-50.

Mazzarol, T. (1999), “An examination of the factors critical to the establishment and

maintenance of competitive advantage for educational service enterprises within international markets”,unpublished PhD thesis, Curtin University of Technology, Australia.

Mazzarol, T.W. (1998), “Critical Success Factors for International Education Marketing”,

International Journal of Education Management, Vol. 12, No. 4, pp. 163-75. Mazzarol, T.W., Choo, S. and Nair, V.S. (2001a), Australia and the Indian Postgraduate

Science and Technology Market. Examining Why Indian Students Choose to Study in Countries Other than Australia, Australian Education International, Department of Education, Training and Youth Affairs, Commonwealth of Australia, Canberra.

Mazzarol, T., Kemp, S. and Savery, L. (1997), International Students Who Choose Not to

Study in Australia: An Examination of Taiwan and Indonesia, Australian International Education Foundation, Canberra.

Mazzarol, T., Soutar, G.N. and Tien, V. (1996), "Education Linkages Between Canada and

Australia: An Examination of the Potential for Greater Student Flows", Unpublished Paper, Institution for Research into International Competitiveness, Curtin Business School, Perth.

Mazzarol, T., Soutar, G.N. and Thein, V. (2000), “Critical Success Factors in the Marketing

of An Education Institution - A Comparison of Institutional and Student Perspectives”, Journal of Marketing for Higher Education, Vol. 10, No. 2, pp. 39-57.

Mazzarol, T., Soutar, G.N. (2002), ““Push-pull” Factors Influencing International Student

Destination Choice”, The International Journal of Educational Management, Vol. 16, No. 2, pp. 82-90.

Mazzarol, T.W., Soutar, G.N., Smart, D. and Choo, S. (2001), Perceptions, Information and

Choice: Understanding How Chinese Students Select a Country for Overseas Study, Australian Education International, Department of Education, Training and Youth Affairs, Commonwealth of Australia, Canberra.

McMahon, M.E. (1992), “Higher Education in a World Market: An Historical Look at the

Global Context of International Study”, Higher Education, Vol. 24, No. 4, pp. 465-482.

Meyers-Levy, J. (1988), “The Influence of Sex Roles on Judgment”, Journal of Consumer

Research, Vol. 14, pp.522-530.

139

Meyer-Levy, J. and Mahjeswaran, D. (1991), “Exploring Difference in Males’ and Females’

Processing Strategies”, Journal of Consumer Research, Vol. 18, pp. 63-71. Meyer-Levy, J. and Sternthal, B. (1991), “Gender Differences in the Use of Message Cue and

Judgments”, Journal of Marketing Research, pp. 84-98. Miller, E.I., (1997), “Parents Views on the Value of a College Education and How They Will

Pay for It”, Journal of Student Financial Aid, Vol. 27, No. 1, pp. 20. Molly, N.N.L. (2006), “Centralized Decentralization in Malaysia Education”, Educational

Decentralization, Springer, Netherlands. Molly, N.N.L.(1999), “Education in Malaysia: Towards Vision 2020”, School Effectiveness

and School Improvement, Vol. 10, No. 1, pp. 86-89. Molly, N.N.L.(2004), “Global Trends, National Policies and Institutional Responses:

Restructuring Higher Education In Malaysia”, Educational Research for Policy and Practice, Vol. 3, pp. 31-46.

Murphy, P. (1981), “Consumer Buying Roles in College Choice”, College and University,

Vol. 56, pp. 140-150. Nguyen, N. and LeBlanc, G. (2001), “Image and Reputation of Higher Education Institutions

in Students Retention Decision”, The International Journal of Educational Management, Vol. 15, No. 6, pp. 303-311.

Noble, M.S. (1986), “Marketing Programs at Colleges and Universities: A Progress Report”,

College and University, Vol. 61, No. 4, pp. 318-326. Nora, A. and Cabrera, A.F. (1992), “Measuring Program Outcomes: What Impacts are

Important to Assess and What Impacts are Possible to Measure ?” Paper Prepared for the Design Conference for the Evaluation of Talent Search. Washington. D.C.: Office of Policy and Planning. U.S. Department of Education.

Nunnaly, J.O. (1978), Psychological Testing: A Practical Approach to Design and

Evaluation, Thousand Oaks: Sage. Ogbuehi, A. O. and Rogers, H. P. (1990), “Recruitment for Higher Education: Targeting the

Excellent High School Student”, Journal of Marketing for Higher Education, Vol. 3, No. 1, pp. 67-77.

Oosterbeek, H., Groot, W. and Hartog, J. (1992), “An Empirical Analysis of University

Choice and Earnings”, The Economist, Vol. 140, No. 3, pp. 293-309. Ortinau, D. and Anderson, R. (1986), “College Students’ Post-Purchase Educational

Satisfaction/Dissatisfaction Decision Process: A Conceptual Model”, AMA Educator’' Proceedings, Chicago, IL.

140

Ortinau, D., Anderson, R. and Klippel, R. (1987), “The Impact of Student Involvement and Expectancy Beliefs on Course/Faculty Evaluations,” AMA Educators' Proceedings, Chicago, IL, pp. 266-271.

Pallant, J.F. (2007), SPSS Survival Manual, 3rd Edition, Open University Press, United

Kingdoms. Paramewaran, R. and Glowacka, A.E. (1995), “University Image: an Information Processing

Perspective”, Journal of Marketing for Higher Education, Vol. 6 No. 2, pp. 41-56. Parasuraman, A., Zeithaml, V. and Berry, L. (2004), “SERVQUAL: A Multiple-item Scale

for Measuring Customer Expectations of Service Quality”, Journal of Retailing, Vol. 64, No. 1, pp. 5-6.

Patterson, P., Romm, T. and Hill, C. (1998), “Consumer Satisfaction As a Process: A

Qualitative, retrospective Longitudinal Study of Overseas Students in Australia”, Journal of Professional Services Marketing, Vol. 16, No. 1, pp. 135-57.

Paulsen, M.B. (1990), College Choice: Understanding Student Enrollment Behavior, ASHE-

ERIC Higher Education Report No. 6, Washington, D.C.: School of Education and Human Development, George Washington University.

Peng, Z., Lawley, M. and Perry, C. (2000), “Modeling and Testing Effects of Country,

Corporate and Brand Images on Consumers’ Product Evaluation and Purchase Intention”, Paper Presented at the ANZMAC 2000 Visionary Marketing for the 21st Century: Facing the Challenge Conference.

Perna, L. W. (2000), “Differences in College Enrollment Among African Americans,

Hispanics and Whites’, Journal of Higher Education, Vol. 71, No. 1, pp. 117-141. Peters, M. (1992), “Performance Indicators in New Zealand Higher Education: accountability

or control ?”, Journal of Education Policy, Vol. 7 No. 3, pp. 267-83. Pimpa, N. (2003), “The influence of Family on Thai Students’ Choices of International

Education”, The International Journal of Educational Management, Vol. 17 No. 5, pp. 211-219.

Price, I., Matzdorf, L. and Agahi, R (2003), "The Impact of Facilities on Student Choice of

University", International Journal of Educational Management, Vol. 21 No. 10, pp. 212-222.

Qureshi, S. (1995), “College Accession Research: New Variables in an Old Equation”,

Journal of Professional Services Marketing, Vol. 12 No. 2, pp. 163-70. Rathmell, J.M. (1966), “What is Meant by Services ?”, Journal of Marketing, Vol. 30,

October, pp. 32-36. Roberts, K. (1984), School Leavers and Their Prospects: Youth in the Labour Market in the

1980s, Open University Press, Milton Keynes.

141

Rosen, D.E., Curran, J.M. and Greenlee, T.B. (1998), “College Choice in Brand Elimination Framework: The High School Students’ Perspective”, Journal of Marketing for Higher Education, Vol. 8, No. 3, pp 73-92.

Russell, C. (1980), Survey of Grade 12 Students’ Postsecondary Plans and Aspirations,

Manitoba: Canadian Department of Education. Rust, R. and Zahorik, A. (1993), “Customer Satisfaction, Customer Retention and Market

Share,” Journal of Retailing, Vol. 69, Summer, pp. 145-156. Schab, F. (1974), “Reasons for Attending College as Reported by Female Students”, Florida

Journal of Educational Research, Vol. 16, pp. 55-58. Schweitzer, S. (2006), “N.E. Colleges Preparing for Drop in Local Students”, Boston Globe,

Jan. 24, 2006, A.1. Sekaran, U. (2003), Research Methods for Business: A Skill Building Approach, 4th edition,

John Wiley & Sons Inc., U.S. Seneca, J. and Taussig, M. (1987), “The Effects of Tuition and Financial Aid on the

Enrolment Decision at a State University”, Research in Higher Education, Vol. 26, August, pp. 337- 62.

Sethna, B.N. (1982), “Extensions and Testing of Importance-performance Analysis”,

Business Economics, September, pp. 28-31. Sewell, W., and Shah, V. (1968), “Social Class, Parental Encouragement, and Educational

Aspirations”, America Journal of Sociology, Vol. 73, pp. 559-572. Shank, M.D. and Beasley, F. (1998), “Gender Effects on the University Selection Process”,

Journal of Marketing for Higher Education, Vol. 8, No. 3, pp. 63-71. Sheppard, L., Schmit, J., and Pugh, R. (1992), “Factors Influencing High School Students’

Changes in Plans for Post Secondary Education: A longitudinal Study”, Paper Presented at the Annual Meeting of the American Educational Research Association, San Francisco.

Sidin, M.S., Hussin, S.R. and Tan, H.S., (2003), “An Exploratory Study of Factors

Influencing the College Choice Decision of Undergraduate Students in Malaysia”, Asia Pacific Management Review, Vol. 8, No. 3, pp. 259-280.

Smith, D., Scott, P. and Lynch, J. (1995), The Role of Marketing in the University and

College Sector, Heist, Leeds. Sohail, M.S., Rajadurai, J. and Rahman, N.A.A. (2003), “Managing Quality in Higher

Education: A Malaysian Case Study”, The International Journal of Educational Management, Vol. 17, No. 4, pp. 141-146.

142

Sohail, M.S. and Saeed, M. (2003), “Private Higher Education in Malaysia: Students’ Satisfaction Level and Strategic Implications”, Journal of Higher Education Policy and Management, Vol. 25, No. 2, pp 173-181.

Somers, P., Cofer, J. and Putten, J.V. (1999), “The Influence of Early Aspirations and

Attitudes on Postsecondary Attendance”, American Educational Research Association Conference, Montreal, Canada.

Soutar, G. and Turner, J. (2002), “Students’ Preferences for University: a Conjoint Analysis”,

The International Journal of Educational Management, Vol. 16, No. 1, pp. 40-45. Srikatanyoo, N. and Gnoth, J. (2002), “Country image and international tertiary education”,

Journal of Brand Management, Vol. 10 No. 2, pp. 139-46. St. John, Edward, P., Michael, B., Paulsen and Deborah, F.C. (2005), “Diversity, College

Costs, and Postsecondary Opportunity: An Examination of the Financial Nexus Between College Choice and Persistence for African Americans and Whites”, The Journal of Higher Education, Vol. 30, pp. 301-315.

Stage, F.K. and Hossler, D. (1989), “Differences in Family Influences on College Attendance

Plans for Male and Female Ninth Graders”, Research in Higher Education, Vol. 30, No. 3, pp. 301-315.

Stanton, W.J. (1974), Fundamentals of Marketing, McGraw Hill, Tokyo. Stefanie. D., Teresa, L. and Danielle, L. (20060, “Higher Education Marketing Concerns:

Factors Influence Students’ Choice of Colleges”, The Business Review, Cambridge, Vol. 6, No. 2, pp. 101-110.

Swinyard, W.R. (1980), “Strategy Development With Importance/Performance Analysis”,

Journal of Bank Research, Vol. 10 No. 4, pp. 228-234, Tabachnick, B.G. and Fidell, L.S. (2007), Using Multivariate Statistics, 5th Edition, Boston:

Pearson Education. Teichler, V. (2004), “The changing debate on internationalization of higher education”,.

Higher Education, Vol. 48 No. 1, pp. 5-26. Thomas, M.S., Adams and Birchenough, A. (1996), “Students Withdraw From Higher

Education”, Educational Management and Administration, Vol. 22, No. 2, pp. 207-221.

Tierney, M. (1983), “Student College Choice Cets: Toward An Empirical Characterization”,

Research in Higher Education, Vol. 18, pp. 271-284. Tillery, D. (1973), Distribution and Differentiation of Youth: A Study of Transition from

School to College. Cambridge, MA: Ballinger Publishing Company. Tillery, D., and Kildegaard, T. (1973), Educational Goals, Attitudes and Behaviors: A

Comparative Study of High School Seniors, Cambridge, Mass.: Ballinger.

143

Topor, R. (1983), Marketing Higher Education: A Practical Guide, Washington, DC: Council

for Advancement and Support of Education. Turner, J.P. (1998), “An Investigation of Business Undergraduates’’ Choice to Study at Edith

Cowan University”, Unpublished Research Report, Edith Cowan University, Perth. Turner, P., Anne, C. (2007), “Why University Student Choose an International Education: A

Case Study in Malaysia”, International Journal of Education Development, Vol. 27, No. 2, pp. 235-246.

Vaira, M. (2004), “Globalization and Higher Education Organizational Change: A

Framework for Analysis”, Higher Education, Vol. 48, No. 4, pp. 483-510. Wajeeh, E.M. and Micceri, T. (1997), “Factor Influencing Students’ College Choice at

Traditional and Metropolitan Universities”, Paper Presented at the Annual Forum of the Association for Institutional Research, Orlando, FL.

Walther, E. (2000), The Relationships Between Student Satisfaction and Student Retention in

Higher Education, Unpublished Dissertation, Faculty of Graduate School, University of North Carolina, Greensboro.

Watson, B.L. (2000), “A Descriptive Study of Enrollment Marketing Strategies for Four-Year

Public Colleges and Universities”, Dissertation Abstracts International, Vol. 61, No. 10.

Webb, M. (1993), “Variables Influencing Graduate Business Students’ College Selections”,

College and University, Vol. 68, No. 1, pp. 38-46. Wilson, K. R., and Allen, W. R. (1987), “Explaining the Educational Attainment of Young

Black Adults: Critical Familial and Extra-familial Influences”, Journal of Negro Education, Vol. 56, No. 1, pp. 64-67.

Zeithaml, V.A., Berry, L.L. and Parasuraman, A. (1996), “The Behavioral Consequences of

Service Quality”, Journal of Marketing, Vol. 60, pp. 31-46. Zeithaml, V.A., Parasuraman, A. and Berry, L. (1985), “Problems and Strategies in Services

Marketing”, Journal of Marketing, Vol. 49, Spring, pp. 33-46. Zusman, A. (1999), Issues Facing Higher Education in the Twenty-First Century, American

Higher Education in the Twenty-First Century, Baltimore, MD: John Hopkins University Press.