ARTICLE FACTORS AFFECTING CONSUMER S PURCHASE INTENTION TOWARDS ONLINE SHOPPING

Final Year Project CS241 Colloqium
22 June 2017, Faculty of Computer and Mathematical Sciences
Factors Affecting the Consumer’s Purchase Intention Towards Online Shopping : A
Case Study Among Students at UiTM Kota Bharu
Ainnul Nadirah Fauzi1
, Nur Fatira Asri2
, Nurul Najwa Rasid3
1,2,3
Faculty of Computer and Mathematical Sciences, Universiti Teknologi MARA Kelantan, Kota Bharu, Kelantan,
Malaysia
ainnulnadirah96@gmail.com , tirairsa@gmail.com , wawa.rasid1996@gmail.com
Abstract: The main focus of this study was to determine whether there is a significant relationship between the consumer’s
purchase intention and gender, age, website design and security have. Besides, this study aims also to find what is the most
crucial factor that significantly contribute to the consumer’s purchase intention towards online shopping and lastly is to
examine the mean difference between genders towards consumer’s purchase intention of online shopping. The independent
variables that are included in this study were gender, age, website design and security, while the consumer’s purchase intention
as the dependent variable. This study involved 239 respondents by using proportionate stratified sampling and the data was
collected using the questionnaire method and were distributed in the form of Google Docs and administered through
WhatsApp. The methods of data analysis used were Pearson correlation, multiple linear regression, One Way Analysis of
Variance (ANOVA) and two independent sample t-test. The finding shows that there is a moderate relationship between the
age, gender, website design and security with the consumer’s purchase intention. Also, website design and security are the
factors that influence the consumer’s purchase intention while gender and age was not statistically significant. In view of
second objective, website design is the most influencing factors that contribute to the consumer’s purchase intention. Other
than that, the result of two independent t-test showed that there is a mean difference between genders towards consumer’s
purchase intention of online shopping and female students have higher purchase intention compared to male students.
Keywords: Consumer’s Purchase Intention, Multiple Linear Regression, Security, Website Design
1 Introduction
“An increasing number and variety of firms and organizations are exploiting and creating business
opportunities on the Internet” (Liao & Cheung, 2000:299). Albarq (2006) highlighted that the usage of
the internet in Malaysia has developed promptly and has grown into a common way for transaction of
products, services and information. The statistics that has made by Internet users in Malaysia showed
that the internet users have increased rapidly from 3,700,000 in 2010 to 17,723,000 in 2012 (Internet
World Stats, 2013).
According to Jariah, Husniyah, Laily and Britt (2004), with the expansion of educational services
in Malaysia, university students become one of the most important market population for several
reasons. Firstly, this group has money and shopping interests. Moreover, university students have higher
potential of earning a greater income than the other segments of the population. Therefore, if we want
to expand the group of online buyers and the volume of e-commerce, it will be of great significance to
find out the factors which influence students’ intention to shop online. Unfortunately, there are only a
few studies examining students’ intention towards online shopping in the Malaysian environment
(Haque et al., 2006).
Consumer’s purchase intention is strongly influenced by the characteristics of the consumers.
Defeng, Bingchuan, and Li (2006) mentioned that the intention towards online shopping is influenced
by demographic factors such as gender, age and income. Moreover, consumer purchase intention is
mainly based on the website design such as pictures, images, quality information, and video clips of the
products (Lohse & Spiller, 1998). Security is a critical factor in gaining and retaining consumers as the
service users of online shopping since it affect information satisfaction in the Web environment. This
is due to the fact that consumers are concerned about the security of online payment, reliability and
privacy policy of the online store (Gefen, 2000).
In order to gain an insight about this phenomenon and to increase online shopping, it is important
to understand the driving forces towards online shopping intention and to recognize why the students
make their online purchase. There are only few studies have examined the relation among consumer

Ainnul Nadirah Fauzi
purchase intention of online shopping and factors including gender, age, website design and security.
Therefore, it is crucial for the researcher to conduct this study to analyze and identify the factors that
influence the consumer’s purchase intention to shop online.
The objectives of this study are:
i) To determine whether there is a significant relationship between genders, ages, website
design and security towards consumer’s purchase intention of online shopping.
ii) To identify the most significant factor influencing consumer’s intention of online shopping.
iii) To examine the mean difference between gender towards consumers’ purchase intention of
online shopping.
The hypotheses for this study are as follow:
i) H1: There is a significant relationship between gender and consumer’s intention of
online shopping.
ii) H1: There is a significant relationship between age and consumer’s intention of online
shopping.
iii) H1: There is a significant relationship between website design and consumer’s intention
of online shopping.
iv) H1: There is a significant relationship between security and consumer’s intention of
online shopping.
v) H1: Website design is the most significant factor influencing consumer’s intention of
online shopping.
vi) H1: There is a mean difference between genders towards consumer’s purchase intention
of online shopping.
Significant and limitation of the study
There is a lot of study already done regarding consumers’ behavior towards online shopping as
a tool to determine the factors influence it. But only a few studies were done on the hands on of intention
towards online shopping among students especially in Kelantan.
The findings of this study will help the Malaysian marketers to produce their own marketing
strategies or formula to attract the consumers. A clear understanding of consumer’s online shopping
behavior and factors influencing it could help them to fulfill their necessity in an effective manner. It
generates a huge opportunity for the sellers to formulate their own marketing schemes and turn the
potential customer into actual one when they knew the factors affecting consumers to shop.
Apart from that, this study will also increase the knowledge and research in field of online
shopping to students. The information feature of online shopping is important in determine consumers
decision making in terms of whether or not they will shop at the store. Moreover, they will informed
that online shopping can also save their time hugely because not only can fulfill their customers’ needs,
but online shopping also can save their money and time.
The consumers’ awareness of the important role that e-commerce has played in modern information
technology (IT) context also can be enhanced. It will makes the consumers conscious of online shopping
ranges compared to the ones that was offered by traditional shopping method. The result from this study
will be used as a guideline for further research and improvement related to e-commerce, consumer
behavior, and online retail in view to enhance of quality of life among the students in UiTM Kota Bharu
Campus.
Almost every study has some limitations and so as in this research. Although the research has
reached its aims, there were some unavoidable limitations. The study was carried out in UiTM
(Kelantan) Kampus Kota Bharu. In this study, the respondents who participated in answering the
questionnaire are all part of students in the semester March 2018-July 2018 among Faculty of Computer

Factors Affecting Consumer’s Purchase Intention Towards Online Shopping
and Mathematical Science (FSKM) and Faculty of Business Management (BM). From 630 of students,
239 students were selected in this research.
The study was limited only to students of UiTM Kota Bharu. The result from this study was
not representing another institutional academic in Malaysia. Hence, the findings of the study can only
be generalized to the students of UiTM Kota Bharu and are not able to completely reflect the online
shopping intention of the students in the other universities. Further, the respondents cannot be compared
very well, especially in view of ethnicity and age group because the population in UiTM Kota Bharu is
all teenagers and Malay. To conclude, the study has low generalizability. Therefore, any suggested
recommendation may only be practical to the students in the UiTM Kota Bharu.
On the other hand, the measurement instrument constructed might be the limitation in this
study. The consumer’s purchase intention is not explained completely by the predictor variables
(gender, age, website design, and security). It is about only 42.7% of the total variation in consumer’s
purchase intention is explained by the total variation in gender, age, website design and security. The
remaining 57.3% variation of consumer’s purchase intention was unexplained. Thus, it is possible to
have more predictors of consumer’s purchase intention so that the undiscovered factors can be
explained.
2 Literature Review
According to Lee and Overby (2006), the opportunities for online shopping continue to expand
as the number of internet users continues to increase. This internet-based electronic commerce
environment has turned to be the platform for the society to do research about the product that they
intended to buy and to be in contact with the online store to purchase the goods (Kim & Park, 2003).
The main advantage of online shopping is that the consumer can compare products and price through
online since the consumers’ detailed information and multiple choices were provided. It will become
easier to find online the desired product or service as there is more choice and convenience (Butler &
Peppard, 1998).
A Consumer’s purchase intention
According to Ajzen (1991), intention defined as the degree of mindful work that a person will
pursue to accept his/her behaviour; intention is also viewed as one of the motivational mechanisms of
behaviour. Intention of online purchase is the situation when a consumer is eager and anticipates to be
involved in online transaction willingly (Pavlou, 2003). So, it can be said that purchase intention of
online shopping will only happen when a consumer is planning to buy a particular product or use the
service in the shortcoming.
A research conducted by Podar, Donthu and Wei (2009) affirmed that the online purchase intention
is a significant predictor of definite purchasing behaviour because it can evaluate the product and asses
the criteria of the consumers concerning the website quality and information search. Furthermore, the
consumers’ willpower to obtain product or service from an e-commerce business affect online purchase
intention (Choon et al., 2010). They tend to view the website with the intention to purchase when they
are more get use with the businesses of e-commerce (Forsythe & Shi, 2003; Gefen & Straub, 2004).
B Factors contribute to online shopping
i. Demographic Factor
A study conducted by Gupta (2015) found that the majority of the customers that use online
shopping is between the ages of 18 to 25. According to this study, this situation is due to the
technological revolution that has been rapidly increasing among the teenagers population and they are
capable to use them for their good compare to the other age group because most of the 35 above group
usually have deficiency of sufficient information of technology. In a recent study conducted among the

Gotland University students, the result was showed that the respondent who has the age limit between
21 to 30 is more familiar to shop online (Sultan & Uddin, 2011).
Nagra and Gopal (2013) also found that gender as one of the demographics factor that
affect online purchase of consumers. According to this study, females are more persuasive to
be attracted towards the promotion offered by the online retailers and are more impulsive
buyers as compared to males. Moreover, a concept of rising working woman has also enhanced
it (Nagra & Gopal, 2013). Gupta’s (2015) study found that female is the majority involved in
online shopping and this provides a broad idea of the sex proportion who is more likely to shop
online.
Bhatnagar et al. (2000) discovered that there is no difference in the intention to purchase
online between males and females, but there were differences in the product categories that are
purchased online. Griffin and Viehland (2011) also stated that there is no significant difference
in the perceived risks related with online shopping in different product categories between
males and females.
ii. Website Design
Sultan and Uddin’s (2011) research affirmed that the website design or features is the one of
the influencing and attractive factor among four factors (convenience, time saving, security, website
design) that influence the online customers in Gotland to consume shop online. To be added to the
research, Sultan and Uddin (2011) also stated that the consumers believed that the way of the products
displayed with various pictures from different positions in the website has motivated them to shop
online.
Li and Zhang (2002) highlighted that website quality significantly affect intention of customer
to shop online. Consequently, the purchasing attitudes and behavior of the consumer can positively
influenced by upgrading website quality, hence lead to increased regularity of the initial purchase and
the consumers to make purchase all over again.
iii. Security
Security is another main factor that affects consumers to purchase online. A study conducted
by Bhatnagar and Ghose (2004) claimed that there is a majority of online shoppers who don’t prefer to
purchase online because they concerned about the security of the sensitive and detailed information.
This causing security becomes one of the aspect which limits buying online. Cuneyt and Gautam (2004)
revealed that trust was being secured as a trustworthy shopping channel in online shopping with
advancement of technology, and frequent online shopping on the web.
In that sense, online shopping can be a factor of discouragement among online customers and
directly can influence their purchase intention. Both new and experienced users of internet agree that it
has been an issue for them to risk perceptions regarding Internet privacy and security (Miyazaki &
Fernandez, 2001).
3 Methodology
A Population and sample
Population is the entire group of people, events, or things of interest that the researcher wishes
to investigate while target population refers to the entire group of individuals or objects to which
researchers are interested in generalizing the conclusions. By considering time factor, the researcher
had narrowed down the target population to specific area. This study focused on the undergraduate
students of UiTM Kota Bharu which consists of students from semester 2 until semester 7 from two
faculties; Faculty of Computer and Mathematical Science (FSKM) and Faculty of Business
Management (BM). These individuals are from various backgrounds in term of age, courses and their

current semester. The total number of students in UiTM Kota Bharu is 630 and these students had been
chosen to fulfill the objective of this study. The details about the population size are illustrated in the
table 1.
To determine the appropriate sample size of the population for this study, the researchers use
Raosoft software. The Raosoft sample calculator is basically a software that primarily calculates or
generates the sample size of a research or survey and it include or consider the confidence level,
response distribution and the margin of error.
The result of the sample size shown in Raosoft is 239 students. The sample of students from
UiTM Kota Bharu had been chosen to make inferences about a population. A proportionate stratified
random sampling technique was used in this study where the sample size of each stratum is
proportionate to the population size of the stratum. The minimum sample required for each faculty was
shown in the Table 2.
Table 1 : total number of students Table 2: minimum sample required each faculty
Faculty Total Number
of Students
Business Management
(BM)
297
Computer and
Mathematical Science
(FSKM)
333
Total 630
B Research design
This study regarding the consumers’ intention towards online shopping is a cross-sectional
descriptive design because the researcher wants to draw a picture of the topic as what are the reasons
that encourage the activity of online shopping among the consumers. The data was collected at one
point in time. This study design provides a quick snapshot of what’s going on with the variables of
interest for the research problem. This study includes different groups of respondents who differ in the
variable of interest but share same other characteristics. For this study, the variable of interest was
gender, age, website design and security for the researcher wants to see whether this factors influence
the consumer’s purchase intention.
Generally, there are two types of research method which are quantitative and qualitative. This study
use quantitative method as it is a precise way. Creswell (1994) highlighted that when selecting research
method, time is vigorous element for decision making. Quantitative research can be faster as compare
to qualitative as it is possible to forecast the time schedule, but qualitative can be relatively long in
duration (Saunders, Lewis, and Thornhil ,2000). Research projects that normally done for academic
reasons are limited to time. Since this study is also for academic purpose and have a limited time, so
that is why the researchers chose quantitative approach.
C Data collection method
Data collection methods are an integral part of research design and it is an identification of method
that allows the highest response rate. For the purpose of this study, primary data has been collected,
analyzed and presented. The primary data and other relevant information were collected through a
questionnaire. A self-administered questionnaire was used in this study. The questionnaires were
distributed to the respondents in the form of Google docs and administered through Whatsapp. The
questionnaires were distributed individually to all 239 students from 22nd
April 2018 until 26th
April
2018. All the questionnaires were collected back by the researcher after one week.
Faculty Minimum Sample
Required
Business Management
(BM)
113
Computer and
Mathematical Science
(FSKM)
126
Total 239

D Method of data analysis
The summary of the method of analysis that the researcher used was illustrated in the table below:
Table 3: The summary of method of analysis
Objective Analysis
To determine whether there is significant
relationship between demographics, website
design and security towards intention of online
shopping
Multiple Linear Regression
To identify the most significant factor
influencing online shopping
Multiple Linear Regression
To examine the mean difference between male
and female towards consumers’ purchase
intention of online shopping
Independent T-Test
E Theorettical framework
Figure 1 : Conceptual Framework
The framework attempts to examine the interrelationships among gender, age, website design,
security and purchase intention. There are several factors influence the consumer’s intention towards
online shopping and the researcher choose to focus on the four major factors which are gender, age,
website design and security.
Gender denotes to the gender of the respondent while age refers to the respondent’s age when
the study was conducted. The independent variable of website design refers to the features of the
websites that focused on the content of the information, the presentation of the information, the
interaction between customers and venders, the navigation and searching mechanism and so forth.
Website design features can be viewed as the factor that contribute to the internet user’s satisfaction
with a website.
Security is a concern for consumer who makes online purchases. Customers’ willingness to
purchase online is greatly affected by consumer’s trust in giving their personal particular details and
security of online payment through credit card online. These factors are found to influence consumers’
intention towards online shopping.
Purchase intention is a consumers’ intention to shop online. It refers to their willingness to
make purchases over the internet. Commonly, this factor is measured by consumers’ willingness to buy
and to return for additional purchases. Consumers’ intention to shop online is positively associated with
demographics, website design and security.

4 Results
A Reliability analysis
The result of reliability analysis for pilot and actual study is shown in the Table 4.
Table 4: Summary result of reliability analysis
Variables Number of items Cronbach Alpha
Website Design 6 0.831
Security 7 0.807
Purchase Intention 7 0.831
From Table 4, there are no items have been deleted as the values have fulfilled the requirement
of over 0.70 as suggested Nunnaly (1978). The internal consistency of all variables (website design,
security and purchase intention) indicated that all items remained good. Subsequently, all indicators
were used for data collection. These values, being above 70% or 0.7, show that the questionnaire was
reliable in collecting the information and it was designed for consistently over time and across people.
The researcher proceeds with other analysis.
B Descriptive analysis
i Gender
The gender distribution among the respondents in this study is illustrated in the figure below.
The majority of the respondents are female where 193 of them are participated in this research (80.75%).
The balance 46 respondents are male (19.25%).
Figure 2 : Distrubution of Gender Figure 3 : Distribution of age
ii Age
In view of age, the majority of the respondents are the students from the age of 22-24 years
(79.92%). 46 respondents are from the age of 20-21 years old (19.25%) and the balance 2 respondents
are from the age of greater than 25 years old (0.84%).
iii Course
From Figure 4, approximately 54.39% of the respondents are from Faculty of Computer and
Mathematical Science (FSKM) and about 45.61% of the respondents are from the Faculty of Business
Management (BM).

iv Semester
From 239 respondents that participated in this study, a total of 110 respondents are from
semester 6, 55 respondents from semester 5, 31 respondents from semester 4 and 28 respondents from
semester 2. 9 respondents from semester 7 and 6 respondents from semester 3 are also participated in
this research.
Figure 4 : Distribution of gender Figure 5 : Distribution of semester
C Online shopping data
Table 5 was the summarized the online shopping data of the respondents that participated in
this research. The independent variable; website design and security are analyzed as well as the
dependent variable which is purchase intention.
Table 5: Descriptive statistics of the online shopping data
N Minimum Maximum Mean Std. Deviation
Purchase
Intention
239 2.14 5.00 4.1243 0.49789
Website
Design
239 2.33 5.00 4.1604 0.51070
Security 239 2.14 5.00 3.8081 0.57337
From Table 5, the lowest mean score of 3.8081 is the security and this showed that the respondents
neither agreed nor disagreed with the indicator that represent security. Purchase intention with the mean
score of 4.1243 and website design with the mean score of 4.1604 showed the respondents agreed with
the indicator that represent purchase intention and website design respectively. The findings displayed
acceptable variability within the data set as the standard deviation fell between 0.49789 and 0.57337.
Thus, it shows that the respondents have different point of view regarding the studied variables.
D Model adequacy checking
For the model adequacy checking, the researchers checked the model whether the assumption
of the multiple linear regression were fulfilled or not. Before proceeding with further analysis, the
assumptions of the error terms need to be satisfied.
0
20
40
60
80
100
120
distribution of
semester
distribution of
semester

Figure 6 : Graph of Normal P-P Plot Figure 7 : Graph of Constant Variance of Error Terms
Based on Figure 6, the normal probability plot of residual shows that the distribution of the
residuals is lying approximately to the straight line. Therefore, the residuals have normal distributions.
Normality assumptions are satisfied.
Based on Figure 7, the scatter plot of residual versus predicted values are randomly scattered
and do not shows any obvious pattern. Therefore, the residuals have a constant variance. The
homogeneity assumptions of the error variance are not violated.
Figure 8 : Graph of Residual versus Order Cases Figure 9 : Correlation Matrix
Based on Figure 8, the scatter plot of residual versus order cases are randomly scattered and do
not shows any obvious pattern. Thus, it can be said that the error terms are identically independent.
Based on the correlation matrix in Figure 9, the relationship of the dependent and independent
variable were shown. Scatterplot of purchase intention versus website design showed that there is a
positive linear relationship between purchase intention and website design. While the scatterplot of
purchase intention versus security also showed that there is a positive linear relationship between
purchase intention and security. Hence, all the independent variables have a linear relationship with the
dependent variable.
Multicollinearity refers to a situation in which two or more explanatory variables in a multiple
regression model are highly linearly related. To access the multicollinearity, when Variance Inflation

Factor (VIF) is greater than 10 and Tolerance (TOL) is less than 0.1, then it can be said that
multicollinearity exist.
Table 6 : Table of Multicollinearity
Variables Collinearity Statistics Findings
Tolerance VIF
Website_Design 0.660 1.509 No multicollinearity
Security 0.660 1.509 No multicollinearity
From Table 6, all the Tolerance values were greater than 0.1 and the VIF values were below
than 10. Thus, the results clearly indicates that all the independent variables were not correlated to each
other. Therefore, multicollinearity problem does not exist.
In multiple linear regression, there must be a linear relationship between the outcome and
predictor variable. To assess the linearity of regression function, the researcher plotted the scatterplot
to check whether there is a linear or curvilinear relationship.
E Goodness of fit
The goodness of fit of a statistical model defines how well it fits a set of observations.
It basically summarizes the inconsistencies between the observed and the expected values
within the model.
i Coefficient of determination
Table 7 shows that there is a moderate positive relationship between variables Website Design,
Security and Purchase Intention (R=0.654). For variation, 42.7% of total variation in the Purchase
Intention was explained by the total variation in all independent variables (Website Design, and
Security). The remaining 57.3% was explained by the other factors.
Table 7 : Table of R-Square Table 8 : Table of Significant of the Model
R R
Square
Adjusted
R Square
0.654 0.427 0.422
ii Significant of the model
Table 8 shows the Analysis of Variance (ANOVA) for the regression model. The F-Statistic
value is 88.030. The p-value for the model is 0.000. Since the p-value is less than the significance level
(0.05), it indicated that the regression model is statistically significant.
F Pearson correlation coefficient
Table 9 shows the correlation among the variables website design, security and consumer’s
purchase intention.
Table 9 : Table of Correlation
Website
design
Security
Consumer’s
purchase
intention
Sig. (2 tailed) 0.000 0.000
Pearson
correlation
0.590 0.572
N 239
Source of
Variation
F Statistic Significant p-value
Regression 88.030 0.000

Table 9 shows that website design and security are the only significant factors that have a
relationship with the consumer’s purchase intention of online shopping since their significant values
are less than 0.05. Website design and security have a positively moderate relationship with the
consumer’s purchase intention.
G Multiple Linear Regression
For the first objective and second objective, the beta coefficient value was computed and
analyzed. The result for the analysis was shown in the Table 10.
Table 10 : Coefficient for each Variable
Model
Unstandardized Coefficients
Sig.
B
(Constant) 1.272 0.000
Website_Design 0.432 0.000
Security 0.277 0.000
Table 10 portrayed the degree of relationship that affected the purchase intention. The most
significant factor that contributes to the purchase intention of online shopping is website design factor
since its beta coefficient value is the largest which is 0.432. With the beta coefficient value 0.277,
security factor comes second in term of contribution to the dependent variable. Age and gender do not
contribute to the consumer’s purchase intention. Therefore, the relationship between dependent and
independent variables for this research can be explained by the following equation:
Purchase intention = 1.272 + 0.432 (Website Design) + 0.277 (Security) (1)
H Two independent sample t-test
A two independent sample t-test was used to analyze the significant difference between genders
on a consumer’s purchase intention.
i Coefficient of determination
For the equality of variance of this analysis, the researchers conducted Levene’s Test.Table 11
shows that p-value for Levene’s Test is 0.094. The p-value is greater than significance value (0.05).
Thus, we can conclude that the population variances for male and female respondents are equal. The
assumption of homogeneity of error variance is not violated.
Table 11 : Table of Levene’s Table 12: Table of T-Test for Equality of
Levene’s Significant
Value
0.094
ii Test for equality means
The t-test for equality means was conducted by the researchers and it was portrayed in the Table
12.Table 12 shows the result for two independent sample t-test. Based on t-test value, it does indicate
that the mean of purchase intention for the first group which is male, is significantly lower than the
mean for the second group, female. Since the p-value is equal to 0.018, it can be concluded that the
mean of purchase intention for male and female is significantly different. Therefore, female students
have higher purchase intention compared to male students.
T-Test
Value
Significant Value
Equal
Variances
Assumed
-2.378 0.018

5 Discussion
The demographic information of target respondents was categorized by gender, course, age and
semester. Majority of the respondents were female which consists of 80.75% in this research. The recent
study from Nagra and Gopal (2013) also found that females are the dominator of their study. In their
paper, it is stated that the rising of working woman nowadays had enhanced them to be attracted towards
the promotional product that the online retailer offered. They are more impulsive buyers when compared
to males since they are most likely to be involved in shopping.
As age played an important role affecting the frequency of consumer’s online shopping, this
research proved that the respondents that has taken part are between the age of 22-24 years old are the
majority. UiTM Kota Bharu where this study take place are consist of degree students from semester 2
to 6. So, the majority of the students at UiTM is basically falls in the range of 22-24 years old. A study
conducted by Gupta (2015) found that the majority of the customers that practice online shopping is
between the ages of 18 to 25 years old due to the technological revolution that has been rapidly
increasing among the teenagers population.
In view of course, 54.39% of the respondents are from Faculty of Computer and Mathematical
Science (FSKM) and about 45.61% of the respondents are from the Faculty of Business Management
(BM). This situation is due to the majority of the students in UiTM Kota Bharu are from FSKM
compared to the BM faculty. This can be seen by looking at the population of the students in UiTM
where 52.86% are FSKM students.
In terms of semester, approximately 46.03% of the respondents are from semester 6 are the
majority followed by semester 5 students with 23.01%, while semester 3 are the minority with 2.51%.
This is because, the semester 5 and 6 students are already exposed with the proposal and the actual of
Final Year Project. So, they already knew that their participation in this study are important to the
researchers. Meanwhile, semester 2 students with the minority participation in this study is probably
because of their ignorance and they are not exposed about the importance of this research.
For the dependent variable in this study which is purchase intention, the minimum and
maximum value are 2.14 and 5.00 respectively with 4.1243 value of mean. The higher value of mean
denotes that the respondents are mostly strongly agree with the items asked. Hence, we can conclude
that the respondents are involved actively in online shopping and they are satisfied with it. A research
by Pavlou (2003) stated that online purchase intention is the situation when a consumer is eager and
anticipates to be involved in online transaction willingly. The standard deviation value of variable
purchase intention suggests that most of the respondents answer are near to the mean value. A research
conducted by Podar, Donthu and Wei (2009) affirmed that the online purchase intention is a significant
predictor of definite purchasing behaviour because it can evaluate the product and asses the criteria of
the consumers concerning the website quality and information search.
Website design variable also showed that the majority of the respondents are strongly agree
with the items asked. This can be seen at the mean value of it is 4.1604 with the minimum and maximum
value are 2.33 and 5.00 respectively. This situation literally interpreted that website design played a
crucial role in assuring the quality of online shopping. The low value of standard deviation (0.51070)
means that the respondents answer are near to the mean value. A similar research conducted by Liang
and Lai (2000) said that the website design quality has an important impacts on consumer choice of
electronic stores. Bagozzi’s (1992) research highlighted that website needs to be well-designed, so that
consumers can adjust to it quickly and do their shopping errands conveniently and effortlessly.
Nevertheless, security variable’s analysis result showed that the respondents are not certain or
sure with the question asked. With the mean value of 3.8081 where the minimum and maximum value
are 2.14 and 5.00 respectively has proven that the consumers are not entirely feels secure when shop
online. The standard deviation value of 0.57337 illustrated that the respondents answer are near to the
mean value. The value has strengthen the statement that Matea and Vojvodic (2014) claimed in their
paper that the customer’s concerned mainly refer to the risks related to the online transaction, such as

revealing private information, the possibility of credit card fraud, and the inability to touch and see the
product itself before make a purchased.
6 Conclusion
Online shopping is becoming more popular nowadays thanks to the advancement of internet and
easy accessible of internet usage. So, for the online retailer, understanding the customer’s need and
demand is a must if they want to step up their game in their business. Therefore, this research was
conducted to provide an in-depth understanding and investigation on factors that affecting the
consumer’s purchase intention towards online shopping. This research had achieved the objectives
which are to identify the relationship between consumer’s purchase intention and gender, age, website
design and security. The second objective for this study is to pinpoint the most significant factor that
contribute to the purchase intention, while the last objective is to examine the mean difference between
genders towards consumer’s purchase intention of online shopping.
The first objective is to find the significant relationship between the consumer’s purchase
intention and demographic factor, website design and security is achieved. The result shown that
website design and security are the only variable that influence the consumer’s purchase intention
towards online shopping. This is supported by Li and Zhang’s (2002) research, where they highlighted
that website quality significantly affect intention of customer to shop online. Consequently, consumer
attitudes and behavior can be positively influenced by improving website quality, thus leads to surged
the frequency of initial purchase and repurchases on the part of consumers.
Bhatnagar and Ghose (2004) said that security is one of the elements that influence the
consumers not to shop online. This is because, they claimed that there is a group of consumers who
don’t like to purchase goods over the internet because of their thoughts about the safety of their private
information. On the contrary, in view of gender, Nagra and Gopal (2013) found that gender as one of
the variables of demographics factor that affect online purchase of consumers.
The second objective which is to find the most significant factor that influence the consumer’s
purchase intention viewed that website design variable is the most crucial factor compared to the other
variables. Website design is one of the significant factors influencing online shopping. Kamariah and
Salwani (2005) claims the consumer intends to shop online over the internet increase when the website
quality is higher. As the website is designed with quality features, it can guide the customers for
successful transactions and attract the customers to revisit the website again (Li and Zhang, 2002).
The third objective of this study is to examine the mean difference between male and female
towards consumer’s purchase intention of online shopping. From the Table 4.11, the result showed that
the p-value is significant where the value is less than 0.05. It indicates that there is a significant
difference between male and female concerning the dependent variable (consumer’s purchase intention
of online shopping. The negative t-value indicates that the mean of purchase intention for the first group
which is male, is significantly lower than the mean for the second group, female. To conclude, female
students have higher purchase intention compared to male students.
According Nagra and Gopal (2013), females are more likely to be attracted towards the
promotional schemes offered by the online retailers and are more impulsive buyers as compared to
males. Moreover, a concept of rising working woman has also enhanced it (Nagra & Gopal, 2013).
Gupta’s (2015) study found that a broad idea of the sex proportion who is more involved in shopping
can be seen when more of the female member involved in online shopping
In an nutshell, the researcher foresee that the findings can benefited the society and online
retailers and help them to have a clear and wide picture about the factors affecting the consumer’s
purchase intention. With all those information the researcher gladly shared, it hopefully will give an
idea or strategies for the online retailers to develop an innovative online marketing strategy so that they
can cater the online shoppers or consumers in Malaysia.

Acknowledgements
First of all, thanks and praise due to almighty Allah S.W.T, the most gracious for what he has
granted and blessing of Allah upon his messenger, Muhammad S.A.W, the seal of prophet and upon his
family and followers for giving us enough time to complete the project.
Here, we would like to thanks to all who contributed to the completion of this research paper.
First, we are greatly appreciated to our organization advisor. Puan Zafarina Fauzi who played a major
role in providing knowledge, information, and valuable guidance and assistance in completing this
research.
Secondly, we would like to thanks our supervisor, Puan Nur Safwati Ibrahim for her full
guidance to complete this research. Without her help and support, this research may not be complete.
We are also would like to take this grateful opportunity to sincerely express our appreciation to
all of the respondents who take part in answering our research questionnaire. A million thanks also to
them because of their sincerity and really appreciate their cooperation for contributing their time to
answer our survey.
Not to be forgotten, this research owes substantial heartfelt thanks and deep gratitude to our
parents and family and for their support and encouragement from now and ever. We are so grateful for
their continuous love, support and prayers to make it possible. Also, to our friends whom always by our
side during the completion of this research. May Allah bless you all and thank you very much.
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