Potential Relationship between Students’ Satisfaction on University

Attributes and Positive or Negative Word-of-Mouth (WOM) and Its

Correlation with Their Recommendations

Imelda Junita

, Fanny Kristine

, Sherlywati

and Rizki Muhammad Sidik

Department of Management, Maranatha Christian University, Suria Sumantri 65, Bandung, Indonesia

1852095@eco.maranatha.edu

Keyword: Attributes of Students’ Satisfaction, Positive and Negative Word-of-Mouth, Students’ Perception,

Recommendation.

Abstract: Prospective students willing to further their education are expected to gather adequate information, compare

and evaluate the benefits and disadvantages of various universities in a competitive academic atmosphere.

One of the numerous ways of gathering information is through Word-of-Mouth (WOM) from family

members, relatives and friends. Positive or negative WOM is generally formed from university students'

experiences. The purpose of this study is to investigate specific attributes likely to enhance students’

satisfaction regarding a university through Word-of-Mouth (WOM). This is a quantitative and qualitative

research with data obtained from 57 students of a private university in Bandung, Indonesia, from a

questionnaire and Focus Group Discussion (FGD). The results showed that students were most satisfied with

the campus facilities and least satisfied with financial policy. Meanwhile, the results of correlation analysis

indicated that 14 attributes had positive correlation significantly, 7 attributes had negative correlation

significantly, and another 7 were not related. Furthermore, FGD was used to extract information on students'

perceptions, opinions, attitudes towards the experiences gained at the university. The results showed a

significant positive correlation between positive WOM and recommendations by students to others, with no

negative WOM. Based on the study, implications for the university are discussed, and suggestion for future

research is provided.

1 INTRODUCTION

Nowadays, the level of competition among

universities in Indonesia, with dominance in those

owned by private organizations, is significantly

increasing. According to Digdowiseiso (2020) in

2018, Indonesia had 345 (88,24%) private

universities and 46 (11,76%) public universities.

High school graduates are now becoming more

discerning in selecting universities to further their

education due to the expenses associated with the

process. However, by gaining admission into a

university, students are able to choose an occupation

that is suitable for their skills, which in turn provides

financial stability and personal satisfaction.

https://orcid.org/0000-0001-7932-6932

https://orcid.org/0000-0002-5974-7606

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https://orcid.org/0000-0001-7058-8928

Furthermore, it is one of the most important steps

toward social and economic welfare in students' lives

because it shapes their career. Therefore, universities

have to attract prospective students while ensuring the

old ones are properly retained. The universities have

to ascertain their services satisfy students'

expectations.

Generally, universities engaged in service

industry, whereby the output cannot be evaluated

before consumption. Expectations on services are not

as apparent as those of tangible products (Özdemir et

al., 2016). Students tend to gather information

regarding the services provided by universities from

their surroundings, such as family members,

relatives, friends and social media. The informal

160

Junita, I., Kristine, F., Sherlywati, . and Sidik, R.

Potential Relationship between Students’ Satisfaction on University Attributes and Positive or Negative Word-of-Mouth (WOM) and Its Correlation with Their Recommendations.

DOI: 10.5220/0010749000003112

In Proceedings of the 1st International Conference on Emerging Issues in Humanity Studies and Social Sciences (ICE-HUMS 2021), pages 160-166

ISBN: 978-989-758-604-0

comment or impression on the services by someone

to others forms Word-of-Mouth (WOM)

communication. This is defined as a strategy used to

share opinions, feelings or experiences that influence

others’ evaluation and intentions. The messages are

either positive or negative, depending on their

individual opinions (Harahap, Hurriyati, Gaffar,

Wibowo, et al., 2018). Therefore, WOM

communication has become an important source in

the service industry that is capable of positively or

negatively impacting people’s behaviour and

decision-making effectively.

Universities usually use various promotional

instruments to fascinate prospective students.

Nevertheless, some of these instruments are unable to

convince prospective students to register to the

universities, particularly in the final decision-making

phase. WOM communication plays a significant role

in affecting students' decision-making process in

selecting a university. In the Asia Pacific, especially

in Indonesia, people mostly rely on third-party

recommendation (Khraim, 2011). WOM

communication is a powerful tool because it is

usually trusted by information recipients (Chen,

2016). Furthermore, suggestions from family

members, relatives and friends are much more

effective than advertisements and publications.

Normally, people tend to trust others’ opinion

because they feel it is proposed independently

without force or encouragement (Khraim, 2011).

During the search phase, prospective students gather

information on universities from the internet or social

media. However, in the selection phase, they prefer to

obtain a tremendous part of off-the-record

information from informal sources, such as from

family members, relatives, friends, etc.

Here, WOM

communication plays an essential role in the

prospective students' decision-making processes to

choose a university (Lehmann, 2017).

There are positive and negative impacts

associated with this means of gathering information.

Positive WOM communication influence prospective

students to select a university, while negative WOM

creates antipathetic impacts. Negative WOM

communication has the ability to destroy the

university’s reputation and discourage prospective

students from registering.

Many previous studies have discussed the effects

of WOM communication on students’ preferences

and how it influences their decision-making

behaviours.

Özdemir et al. (2016) carried out a research to

determine the effect of WOM communication on

prospective university students in Turkey, especially

on emerging needs, collecting information and

evaluating preferences. WOM communication also

influenced students' decision-making behaviours,

particularly after examining satisfaction,

disappointment and complaints.

The study carried out by Harahap et al., Hurriyati,

Gaffar, and Amanah (2018) stated that WOM

communication positively influenced students’

decision in selecting a university in Indonesia. This is

in accordance with the research carried out by

Lehman ( 2017), which stated that traditional WOM

communication had a more substantial impact on

prospective students' preferences than e-WOM. This

is because e-WOM usually has a more substantial

impact during the search phase than the selection.

Chloe (2019) found a positive relationship

between the overall satisfaction of international

students and social experiences in Malaysia through

WOM communication.

Other studies also discussed predictor variables

affecting WOM communication, such as service

quality, students’ satisfaction, reputations and brand

image of a university.

Dora (2016) stated that the service quality of

private universities is needed to provide students

satisfaction. WOM communication is the implication

of service quality mediated by students' satisfaction.

A study by Chen (2016) on students and graduates

of universities in Taiwan found that brand image,

satisfaction and loyalty of students significantly and

positively influenced the sharing of pleasant

experiences and referencing the university to others.

Ong (2017) proved that students' satisfaction had

an influence on WOM and switching behaviour

directly and significantly. This role as a mediating

variable has also indirectly increased the effect of

reputation on WOM and switching behaviour.

The other studies indicated that service quality

increases students' satisfaction and encourage them to

carry out WOM communication with others

(Mestrovic, 2018; Handayanto, 2018).

Khraim (2011) examined students' willingness to

deliver positive WOM communication in Jordan. The

research found that satisfaction, experience and

source, positively influenced WOM communication

directly. Yet, incentives provided by the universities

have not influenced the students to propagate positive

WOM significantly. When students are satisfied, they

tend to spread positive WOM and more likely to make

a recommendation.

Therefore, it is obvious that WOM is powerful,

more relevant and comprehensive because of its

independent trait. WOM communication has

distinctive credibility. In university, positive or

Potential Relationship between Students’ Satisfaction on University Attributes and Positive or Negative Word-of-Mouth (WOM) and Its

Correlation with Their Recommendations

161

negative WOM is influenced by many factors, which

positively or negatively impacts students' behaviour.

2 METHODS

The research questions are identified as follows:

● Which specific attributes of students’ satisfaction

influence positive or negative WOM

communication regarding the university?

● How are students' experiences likely to enhance

their satisfaction and their perceptions of those

experiences?

● Is there any significant relationship between

positive or negative WOM communication with

students’ recommendation on the university to

others?

The research aims to verify the potential

relationship between students' satisfaction with each

university attribute and their positive and negative

WOM communication and to verify the correlation

between positive or negative WOM communication

with students’ recommendations. This research also

aims to explore students' experiences and perceptions

in accordance with their satisfaction.

The combination of both quantitative and

qualitative research methods are used in this study to

provide a better understanding of research problems.

For quantitative analysis, an online questionnaire

with the Likert Scale was developed. In Part I,

participants were asked to rate their satisfaction levels

with 14 attributes of university experiences (1=very

dissatisfied, 7=very satisfied), such as satisfaction

with the lecturers, curriculum, academic advice, etc.

In Part II, participants were asked to rate the levels

they are likely to communicate positive or negative

WOM to others on the attributes of university

experiences (1=very unlikely, 7=very likely). In Part

III, participants were asked to rate the levels of

recommendation, such as recommending a university

to family members, relatives and friends, as the first

choice in the master program (1=very unlikely,

7=very likely). Correlation analysis was used to

analyse the relationships between levels of students'

satisfaction and positive WOM, levels of students'

satisfaction and negative WOM, positive or negative

WOM and recommendations. This online

questionnaire was administered to 57 undergraduate

students of a private university in Bandung,

Indonesia. Furthermore, qualitative analysis with

focus group discussion was conducted to complement

the quantitative analysis.

The validity test was conducted to determine the

validity of the statements and the fidelity of the

measurement. Pearson correlation analysis was used

to test the validity. Pearson correlation coefficient is

a number between -1 and +1 that indicates the level

of linear dependency between variables. Pearson

correlation coefficients of > 0.35 are interpreted as

strongly valid (Oktavia et al., 2018).

There are 14 attributes of university experiences

to be analysed:

1. Lecturers

2. Curriculum

3. Academic Advising

4. Learning Process

5. Online Learning

6. Information Technology

7. Academic Policy

8. Financial Policy

9. Administration Staffs

10. Learning Facility

11. Campus Other Facility

12. Students’ Activities

13. Social Interaction

14.

Career Prospects

Tables 1-3 show the validity tests results for

students’ satisfaction on each attribute (S1-S14),

Positive WOM on each attribute (PWOM) and

Negative WOM on each attribute (NWOM).

Table 1: Validity Test for Students’ Satisfaction Attributes.

Students’

Satisfaction on

Attributes

Coefficient Results

S1 0.744 vali

S2 0.825 vali

S3 0.440 vali

S4 0.535 vali

S5 0.649 vali

S6 0.650 vali

S7 0.838 vali

S8 0.654 vali

S9 0.688 vali

S10 0.795 vali

S11 0.515 vali

S12 0.788 vali

S13 0.728 vali

S14 0.702 vali

Table 1 shows the result of validity test on students’

satisfaction with each attribute. As all the Pearson

correlation coefficient >0.35, all variables of

students’ satisfaction can be interpreted as valid.

ICE-HUMS 2021 - International Conference on Emerging Issues in Humanity Studies and Social Sciences

162

Table 2: Validity Test for Positive WOM.

Positive WOM

on Attributes

Coefficient Results

PWOM1 0.648 vali

PWOM2 0.825 vali

PWOM3 0.717 vali

PWOM4 0.778 vali

PWOM5 0.793 vali

PWOM6 0.823 vali

PWOM7 0.797 vali

PWOM8 0.691 vali

PWOM9 0.770 vali

PWOM10 0.806 vali

PWOM11 0.612 vali

PWOM12 0.746 vali

PWOM13 0.803 vali

PWOM14 0.867 vali

Table 2 shows the result of validity test on

positive WOM of each attribute. As all the Pearson

correlation coefficient >0.35, all variables of positive

WOM can be interpreted as valid.

Table 3: Validity Test for Negative WOM.

Negative WOM

on Attributes

Coefficient Results

WOM1 0.914 vali

WOM2 0.935 vali

WOM3 0.859 vali

WOM4 0.921 vali

WOM5 0.876 vali

WOM6 0.909 vali

WOM7 0.940 vali

WOM8 0.842 vali

WOM9 0.903 vali

WOM10 0.896 vali

WOM11 0.882 vali

WOM12 0.920 vali

WOM13 0.910 vali

WOM14 0.891 vali

Table 3 shows the result of validity test on

negative WOM of each attribute. As all the Pearson

correlation coefficient >0.35, all variables of negative

WOM can be interpreted as valid.

Table 4: Validity Test for Recommendation.

Recommendation Coefficient Results

R1 0.901 vali

R2 0.899 vali

R3 0.958 vali

R4 0.822 vali

Table 4 shows the result of validity test on

recommendation of each attribute. As all the Pearson

correlation coefficient >0.35, all variables of

recommendation can be interpreted as valid.

The next step is the reliability test, which indicates

the consistency of the instrument in measuring a

certain phenomenon (Ursachi et al., 2015). Cronbach’s

Alpha coefficients of the variables were calculated to

determine the reliability of the instrument.

Table 5: Reliability Test.

Variables Cronbach’s Alpha Results

S 0.909 reliable

PWOM 0.943 reliable

WOM 0.982 reliable

R 0.901 reliable

In Table 5., the results indicated that all

Cronbach’s Alpha values were very good and ranged

from 0.901 to 0.982. According to a commonly

accepted theorem, Cronbach’s alpha of 0.60-0.70

represents a reasonable degree of reliability, and

when it is above 0.80, it is in the very good degree

category (Ursachi et al., 2015). This means that all the

variables were consistent or relatively homogenous in

the questionnaire.

3 RESULTS AND DISCUSSION

Table 6 shows the descriptive statistics for students’

satisfaction with attributes.

Table 6: Descriptive Statistics for Students’ Satisfaction.

Students’ Satisfaction

on Attributes

Mean Standard

Deviation

Lecturers 5.81 0.97

Curriculu

5.70 0.96

Academic Advisin

6.14 1.20

Learnin

Process 5.91 1.01

Online Learnin

5.25 1.39

Information Technolo

5.84 1.15

Academic Polic

5.65 1.19

Financial Polic

4.93 1.43

Administration Staffs 5.72 1.13

Learnin

Facilit

5.89 1.10

Campus Other Facilit

6.21 0.92

Students’ Activities 5.63 1.29

Social Interaction 5.89 1.18

Career Prospects 5.75 0.93

Table 6 shows the levels of students' satisfaction

with various attributes of university experiences

Potential Relationship between Students’ Satisfaction on University Attributes and Positive or Negative Word-of-Mouth (WOM) and Its

Correlation with Their Recommendations

163

(1=very dissatisfied to 7=very satisfied). The table

shows that students were most satisfied with campus

and other facilities and least satisfied with financial

policy.

To examine students' perception of each attribute,

they were asked to share their experiences on the

attributes that satisfied or dissatisfied them.

One of the students shared the following

experience on campus other facilities as follows

“Other campus facility, such as food court, it is very

extraordinary with lots of menu variations. Banks and

healthcare are also very helpful. For instance, I

suddenly got sick when I was studying on campus. I

immediately went to the campus health clinic and was

treated. I did not have to pay for it.” Another student

stated that the parking space is quite spacious.

Students also offered suggestions to improve other

campus facilities. For instance, they stated that

“Every classroom needs to be equipped with an air

conditioner, due to the hot weather.” and “The Wi-Fi

network needs to be extended, for students to be able

to access the internet from anywhere."

Few students share dissatisfactions with financial

policy, such as in the following excerpt:” In this

pandemic situation, many students are in financial

distress. University needs to raise tuition discount

rates because students learn from home." and

“Students have to pay the total amount of tuition fee

as stated in the Integrated Administration System

without knowing the details of financial bills.”

In correlations analysis between the levels of

students' satisfaction on attributes and positive

WOM, all the p-values are smaller than the alpha

used, which is 0.05. This means there is a significant

correlation between the students' satisfaction on

attributes and positive WOM, as shown in Table 7.

The correlation analysis results showed that the 14

attributes of satisfaction have positive relationships

with WOM. The signs of all coefficients were

positive, which means the more satisfied students

with the university attributes, the higher their

possibility to communicate positive WOM. These

attributes are lecturers, curriculum, academic

advising, learning process, online learning,

information technology, academic policy, financial

policy, administration staffs, learning facility,

campus, students’ activity, social interaction, and

career prospects.

Regarding the degree of the Pearson correlation,

values of 0 and 1 indicate no correlation and perfect

correlation, respectively. The closer the Pearson

correlation values to +1, the stronger the relationship

between the satisfaction on each attribute with

positive WOM. Meanwhile, when the Pearson

correlation value is closer to 0, it indicates that the

relationship between satisfaction on each attribute

and positive WOM is getting weaker. A correlation

value > 0.5 indicates a fairly strong relationship as a

simple guideline, while a correlation value < 0.5

indicates a weak relationship.

Students' satisfaction with strong relationship and

positive WOM are lecturers, curriculum, online

learning, information technology, academic policy,

financial policy, administration staff, learning

facility, students' activities, social interaction, and

career prospects. Meanwhile, attributes of students'

satisfaction that have a weak relationship with

positive WOM are academic advising, learning

process, and campus other facilities.

Table 7: Correlations between Students’ Satisfaction on

Attributes and Potential Positive WOM Communication.

Attributes r p-value

Lecturers .607 .000*

Curriculu

.687 .000*

Academic Advisin

.431 .001*

Learnin

Process .329 .012*

Online Learnin

.539 .000*

Information Technolo

.545 .000*

Academic Polic

.709 .000*

Financial Polic

.605 .000*

Administration Staffs .569 .000*

Learnin

Facilit

.688 .000*

Campus Other Facilit

.373 .004*

Students’ Activities .641 .000*

Social Interaction .615 .000*

Career Prospects .639 .000*

The correlation analysis results also showed that

the attribute most strongly related to positive WOM

is academic policy, which is represented by the value

of 0.709. Some students expressed their opinions on

academic policy, as follows: “So far, the academic

policy is clearly informed, with adequately structured

academic activities, hence I have no problem with

academic policy.” Interestingly, students were most

satisfied with campus other facilities, however, this

attribute was related most weakly to positive WOM.

Meanwhile, the results of the correlation analysis

between the level of students’ satisfaction on

attributes and negative WOM, as shown in Table 8,

indicates that 7 of the 14 students’ satisfaction on

attributes significantly correlated with negative

WOM. These attributes include lecturers, curriculum,

learning process, academic policy, learning facility,

students’ activities and social interactions. The

correlation results are all negative; therefore,

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164

increasing students' satisfaction on attributes value

decreases their possibility of communicating negative

WOM. The closer the Pearson correlation values to -

1, the stronger the relationship between the

satisfaction on each attribute with negative WOM.

Nevertheless, these 7 attributes of satisfaction have a

weak relationship with negative WOM and

significantly correlated with positive WOM (six

attributes strongly correlated with positive WOM,

including lecturers, curriculum, academic policy,

learning facility, students’ activity and social

interaction). Therefore, students' dissatisfaction with

these 6 attributes resulted in negative WOM weakly

but students’ satisfaction with these attributes

resulted in positive WOM strongly.

The attribute that was related most strongly to

negative WOM is lecturers. Few students shared their

experiences about lecturers, such as “I have both

positive and negative impression on few lecturers.

This is because some lecturers create a pleasant

learning atmosphere. They arranged simulation and

interactive discussion in the class for students to

understand the learning course properly.

Furthermore, students’ efforts were also appreciated.

However, some lecturers did not deliver the learning

course properly.”

On the contrary, students' satisfaction on

attributes including academic advising, online

learning, information technology, financial policy,

administration staffs, campus other facilities, and

career prospects were only related to positive WOM.

Hence, students' satisfaction with these attributes

generated positive WOM but students’ dissatisfaction

with these attributes would not generate negative

WOM.

Table 8: Correlations between Students’ Satisfaction on

Attributes and Potential Negative WOM Communication.

Attributes r p-value

Lecturers -.405 .002*

Curriculu

-.397 .002*

Academic Advisin

-.081 .549

Learnin

Process -.292 .027*

Online Learnin

-.130 .336

Information Technolo

-.243 .068

Academic Polic

-.383 .003*

Financial Polic

-.230 .086

Administration Staffs -.194 .147

Learnin

Facilit

-.351 .007*

Campus Other Facilit

-.210 .117

Students’ Activities -.374 .004*

Social Interaction -.342 .009*

Career Prospects -.149 .267

Table 9 shows the correlation between students’

satisfaction on attributes and positive WOM with a

sig-value of 0.000, which is smaller than the alpha

used of 0.05. This means that there is a significant

correlation between students’ satisfaction on

attributes and positive WOM. The relationship

between students’ satisfaction on attributes and

positive WOM is also positive because the Pearson

correlation value is 0.839. This means that the higher

the levels of students’ satisfaction on attributes, the

greater the levels of possibility of positive WOM.

Meanwhile, the sig value between students’

satisfaction on attribute and negative WOM generally

shows a sig-value of 0.003, which means there was a

significant and negative correlation (Pearson

correlation value of -0.391). Therefore, an increase in

the level of students' satisfaction on attribute leads to

a decrease in negative WOM from the students.

The correlation results between positive WOM

and recommendation shows the sig-value of 0.000,

smaller than alpha 0.05. This indicates a positive

Pearson correlation value of 0.669, which means the

higher the positive WOM, the greater the possibility

of recommendations delivered by students to others.

The correlation result between the negative WOM

with recommendations shows the sig-value of 0.156,

which is greater than alpha 0.05, which means that it

does not show a significant correlation (Pearson

correlation value of -0.190).

Table 9: Correlations between Variables.

4 CONCLUSIONS

In conclusion, this study showed a significant positive

and negative correlation between students'

Potential Relationship between Students’ Satisfaction on University Attributes and Positive or Negative Word-of-Mouth (WOM) and Its

Correlation with Their Recommendations

165

satisfaction on university attributes with WOM. It

means the more satisfied students with the university

attributes, the higher their possibility to communicate

positive WOM. The correlation analysis results

showed that the 14 attributes of satisfaction have

positive relationships with WOM. Furthermore, 11 of

these attributes, namely lecturers, curriculum, online

learning, information technology, academic policy,

financial policy, administration staffs, learning

facility, students’ activities, social interaction, and

career prospect, have strong relationships with

positive WOM. Meanwhile, 3 attributes, namely

academic advising, learning process, and campus

other facilities, have weak relationships with positive

WOM. Seven attributes of satisfaction, including

lecturers, curriculum, learning process, academic

policy, learning facility, student activities and social

interactions, also have a weak relationship with

negative WOM. These results are in accordance with

the research carried out by Palmer (2011), which

stated that some university attributes were associated

significantly with positive WOM but were not

associated significantly with negative WOM, while

some university attributes were associated

significantly with positive and negative WOM.

The policymaker of the university does not have

to improve other facilities because students are most

satisfied with this attribute. However, the university

needs to make a reasonable academic policy because

it was most strongly related to positive WOM. The

policymaker also needs to enhance the attribute of the

lecturer and make sure to improve performance on

this attribute because it tends to reduce negative

WOM.

Future studies need to be carried out on additional

attributes, such as campus scholarship, implementa-

tion of government policy on higher education, or

WOM communication implications on brand image,

reputation, etc.

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