REPORT THE FACTORS INFLUENCE FOOD DELIVERY ...repository.psa.edu.my/bitstream/123456789/2527/1/THE...NURUL SYAZWANI BINTI ZAKARIA 08DPM18F1040 2. NUR SYAFIQA BINTI ROSLI 08DPM18F1057

DIPLOMA IN BUSINESS STUDIES

COMMERCE DEPARTMENT

REPORT

THE FACTORS INFLUENCE FOOD DELIVERY APPLICATIONS USAGE

AMONG STUDENTS OF POLITEKNIK SULTAN SALAHUDDIN ABDUL AZIZ

SHAH DURING MOVEMENT CONTROL ORDER (MCO)

No. NAME MATRIC NO.

1. NURUL SYAZWANI BINTI ZAKARIA 08DPM18F1040

2. NUR SYAFIQA BINTI ROSLI 08DPM18F1057

3. BATRISYIA BINTI SOBIE 08DPM18F1070

4. ANNUR BINTI ABDUL RAZAK 08DPM18F1077

I

DECLERATION OF ORIGINALITY

TITLE: THE FACTORS INFLUENCE FOOD DELIVERY APPLICATIONS USAGE



SESSION: JUNE 2020

1. We, a) NURUL SYAZWANI BINTI ZAKARIA (08DPM18F1040),

b) NUR SYAFIQA BINTI ROSLI (08DPM18F1057),

c) BATRISYIA BINTI SOBIE (08DPM18F1070),

d) ANNUR BINTI ABDUL RAZAK (08DPM18F1077),

Are the final year students of Diploma in Business Studies, Commerce Department,

Politeknik Sultan Salahuddin Abdul Aziz Shah, located at Persiaran Usahawan, Seksyen U1,

40150 Shah Alam, Selangor.

2. We ensure that ‘this project’ and its intellectual properties are original work without

plagiarism from any other sources.

3. In order to fulfil the requirement of being awarded a Diploma in Business Studies, we agree

to release the intellectual properties of the project to the said polytechnic above.

II

Prepared by:

a) NURUL SYAZWANI BINTI ZAKARIA

(Identity Card No.: 000115081112) NURUL SYAZWANI BINTI ZAKARIA

b) NUR SYAFIQA BINTI ROSLI

(Identity Card No.: 001228020724) NUR SYAFIQA BINTI ROSLI

c) BATRISYIA BINTI SOBIE

(Identity Card No.: 000612020900) BATRISYIA BINTI SOBIE

d) ANNUR BINTI ABDUL RAZAK

(Identity Card No.: 001004020776) ANNUR BINTI ABDUL RAZAK

In front of us,

HASNI BINTI HASHIM

As our Supervisor Date: HASNI BINTI HASHIM

III

ACKNOWLEDGEMENT

First for the wonderful opportunities and experiences throughout the five semesters we

went through, we would like to thank Allah SWT. Gratitude for the grace and encouragement

Allah SWT has given us in completing this study, to go through all the journeys of struggle.

With the guidance of Allah SWT, we might successfully solve this research problem together.

A journey toward achieving one of our lifetime goals is to aspire to succeed and complete this

subject.

Our first and deepest appreciation to our supervisors, the supervisor of this research

project, Puan Hasni Binti Hashim, who supervised, assisted and provided what was needed to

lead this project. It is very important to us without her superior and comprehensive knowledge

and experience to generate excellent project performance and therefore also her support. With

much respect and appreciation, thank you Puan Hasni Binti Hashim.

Special thanks also to Dr. Noordini Binti Abdullah, the DPB6043 Business Project’s

research coordinator, for her professionalism and encouragement from the beginning of this

study to the end of this project. Nevertheless, we express our gratitude to our family for their

kind cooperation and motivation that will enable us to complete this project.

Other than that, we would also like to thank all the respondents involved in the success

of this research project for their contribution to spending some time and struggling to cooperate

in the survey questionnaire.

We would like to thank Food Delivery Services in Malaysia who have supported us a

great deal by gathering information about the services offered so that we can conduct research

on their services. We also would like to thank the employees of the Food Delivery Service who

are able to share knowledge during the research with us.

May Allah SWT bless us all.

Thank you.

IV

THE FACTORS INFLUENCE FOOD DELIVERY APPLICATIONS USAGE



NURUL SYAZWANI BINTI ZAKARIA (08DPM18F1040)

NUR SYAFIQA BINTI ROSLI (08DPM18F1057)

BATRISYIA BINTI SOBIE (08DPM18F1070)

ANNUR BINTI ABDUL RAZAK (08DPM18F1077)

SUPERVISOR: PUAN HASNI BINTI HASHIM

Commerce Department

Politeknik Sultan Salahuddin Abdul Aziz Shah, Shah Alam, Selangor

[email protected]

Abstract - Food delivery application is a one of the mobile commerce and it is completed

through the mobile devices, like the smart phones or tablets. The customers can select the food

and make payment online, then the food will be delivered to the customers. During Movement

Control Order (MCO) in Malaysia, demand for food delivery applications increased as their

movement is limited. This purpose of this study is to study the factors influence food delivery

applications usage among students of Politeknik Sultan Salahuddin Abdul Aziz Shah during

Movement Control Order (MCO). Besides, the literature review will look further into the detail

of the effectiveness of using food delivery applications among students. The analysis of

research data will be carry out using Google form software. Data that relate to this assemble

were collected from 357 students from Politeknik Sultan Salahuddin Abdul Aziz Shah. The

result indicate that facilitating conditions had a strongest influence on the factors influence

followed by social influence and habit. Therefore, this research confirms its importance of

social influence, facilitating conditions and habit as a factor in encouraging users to use food

delivery applications. This research could make improvement to the food delivery applications

on how to attract customer among students of Politeknik Sultan Salahuddin Abdul Aziz Shah.

Keywords – food delivery applications, Movement Control Order (MCO), factors influence

mailto:[email protected]

V

TABLE OF CONTENTS

CONTENT PAGE

DECLARATION OF ORIGINALLY I – II

ACKNOWLEDGEMENT III

ABSTRACT IV

TABLE OF CONTENTS V - VII

LIST OF TABLES VIII - IX

CHAPTER 1: INTRODUCTION

1.1 INTRODUCTION 1 – 2

1.2 BACKGROUND OF RESEARCH 2 – 3

1.3 PROBLEM STATEMENT 3

1.4 RESEARCH OBJECTIVE 4

1.5 RESEARCH QUESTION 4

1.6 SCOPE OF RESEACH 4

1.7 SIGNIFICANT OF RESEARCH 5

1.8 DEFINITION OF TERM 5 – 6

1.9 SUMMARY 7

CHAPTER 2: LITERATURE REVIEW

2.1 INTRODUCTION 8

2.2 LITERATURE REVIEW AND HYPOTHESES 8

2.2.1 STUDENTS OF POLYTECHNIC 9

2.2.2 FOOD DELIVERY APPLICATIONS 10

2.2.3 SOCIAL INFLUENCE 11

2.2.4 FACILITATING CONDITIONS 12

2.2.5 HABIT 13

2.3 HYPOTHESES OF THE STUDY 14

2.3.1 SOCIAL INFLUENCE 14

VI

2.3.2 FACILITATING CONDITIONS 14

2.4.3 HABIT 15

2.4 THEORATICAL FRAMEWORK 16

2.5 SUMMARY 16

CHAPTER 3: RESEARCH METHODOLOGY

3.1 INTRODUCTION 17

3.2 RESEARCH DESIGN 17

3.3 DATA COLLECTION METHOD 18

3.3.1 PRIMARY DATA 18

3.3.2 SECONDARY DATA 19

3.4 RESEARCH INSTRUMENT 19 – 24

3.5 SAMPLING TECHNIQUE 25

3.6 DATA ANALYSIS METHOD 26

3.6.1 DESCRIPTIVE METHOD 26

3.7 SCALE MEASUREMENT 27

3.7.1 RELIABILITY TEST 27

3.7.2 PILOT TEST 28

3.8 SUMMARY 29

CHAPTER 4: DATA ANALYSIS

4.1 INTRODUCTION 30

4.2 DEMOGRAPHY PROFILE OF RESPONDENTS 30 – 32

4.3 GOODNESS MEASURE 33

4.3.1 DESCRIPTIVE ANALYSIS 33

4.4 RESEARCH FINDINGS 33

4.4.1 STATISTICAL SUMMARY 33 – 37

4.5 HYPOTHESES TESTING 38

VII

4.5.1 CORRELATION COEFFICIENTS RANGE 38

4.5.2 CORRELATION ANALYSIS 38

4.5.2.1 RELATIONSHIP BETWEEN FOOD

DELIVERY APPLICATIONS AND SOCIAL

INFLUENCE

39


DELIVERY APPLICATIONS AND

FACILITATING CONDITIONS

39


DELIVERY APPLICATIONS AND HABIT 39

4.6 SUMMARY 40

CHAPTER 5: DISCUSSION AND CONCLUSION

5.1 INTRODUCTION 41

5.2 RECAPITULATION OF THE STUDY 41

5.2.1 DISCUSSION OF MAJOR FINDINGS 42

5.3 RECOMMENDATION 43

5.3.1 RECOMMENDATION FOR FUTURE RESEARCH 43

5.3.2 RECOMMENDATION FOR FOOD DELIVERY

COMPANY AND STUDENTS 44

5.4 SUMMARY 45

VIII

LIST OF TABLES

TABLE/FIGURE PAGE

Figure 1 Research Framework 16

Table 3.1 Food Delivery Applications (Dependent Variable) 21

Table 3.2 Social Influence (1st Independent Variable) 22

Table 3.3 Facilitating Conditions (2nd Independent Variable) 23

Table 3.4 Habit (4th Independent Variable) 24

Table 3.5 Alpha Coefficient Range Strength of Association 27

Table 3.6 Reliability Test for 31 Respondents 28

Table 4.1 Demographic Profile 31

Table 4.2 General Information 32

Table 4.3 Overall Descriptive Analysis of the Variable 33

Table 4.4 Statistical Summary (Food Delivery Application) 34

Table 4.5 Statistical Summary (Social Influence) 35

Table 4.6 Statistical Summary (Facilitating Conditions) 36

Table 4.7 Statistical Summary (Habit) 37

Table 4.8 Pearson Correlation Coefficient (r) Strengths 38

Table 4.9 Pearson’s Correlation Coefficients of the Variables 38

IX

REFERENCES 46 – 51

APPENDIX A: 31 SET OF PILOT TEST 52

APPENDIX B: QUESTIONNAIRE 53 – 57

APPENDIX C: CRUCIAL INFORMATION 58 – 64

APPENDIX D: DESCRIPTIVE STATISTICS 65 – 68

APPENDIX E: RELIABILITY TEST 69

APPENDIX F: CORRELATION TEST 70

APPENDIX G: SWOT ANALYSIS 71

APPENDIX H: GANTT CHART 72

1

CHAPTER 1: INTRODUCTION

1.1 INTRODUCTION

An overview of the entire research project was given in this chapter. The goal of the

study is to investigate the factors influencing the use of food delivery applications among

students of Politeknik Sultan Salahuddin Abdul Aziz Shah during the Movement Control Order

(MCO). It consists of eight components of the studies which include the research background,

problem statement, research objectives, research questions, the scope of the research, the

significance of the research, definition of operational terms and summary. The first part of the

study was started with a research background, problem statement and objectives to give a basic

understanding of the overall study. Next, the research question offers arguments and inquiries

which are needed to examine for further investigation. The significance of the study was

explained the importance and contribution of the study. Lastly, the definition of the operational

statement was outlined and ended with the summary.

According to Tang (2020), Prime Minister Tan Sri Muhyiddin Yassin has declared that

the entire country will be on a movement control order starting from 18th March 2020 until

31st March 2020 to deal with the rise in Covid-19 cases. The decision was made under the

Prevention and Control of Infectious Diseases Act 1988 and the Police Act 1967.The

prohibition of movement and mass assembly nationwide would include all religious, sports,

social and cultural activities. The enforcement took place of all places of worship and business

premises must be closed except for supermarkets, public markets, grocery stores, and stores

selling basic necessities. When the movement control order (MCO) was enforced, Malaysians

staying home became dependent on food delivery riders — two major food delivery companies

even increased the number of riders working for them to cope with the spike in demand (Radzi,

2020).

On the other hand, despite the negative influence of COVID-19 significantly affecting

the supply and demand of the catering industry, it has changed the consumption habits of

residents and accelerated the transformation of catering enterprises from traditional in-store

service to online-to-offline service for surviving in the pandemic situation and maintaining

sustainable development (Zhao & Bacao, 2020).

2

The start of Movement Control Order (MCO) saw a large number of people ordering

through food delivery applications such as Grab Food and Food Panda. This comes back to a

trend that has seen changes in the scant few months of Malaysia’s first national-level pandemic

response — food delivery. This was the answer offered by the government during the MCO

for those who, due to various circumstances, were unable to cook while obeying the stay at

home order (Kong, 2020).

1.2 BACKGROUND RESEARCH

This study aims to investigate the factors affecting the use of food delivery applications

during the enforcement of the Movement Control Order (MCO). This analysis is devoted to

the students of Politeknik Sultan Salahuddin Abdul Aziz Shah.

Food delivery applications are becoming more popular in Malaysia with a population

of various races. Application Foodpanda was the first delivery company that started

aggressively in Malaysia in 2012 (Milo, 2018). Foodpanda is one of the leading online food

delivery marketplace and is spread out globally. Foodpanda also has become an instant success

because of their user-friendly, high quality and effective interface (Shona, 2016). After the

success of Foodpanda in food delivery service, there is more competitors try to defeating them

such as GrabFood, dahmakan, Bungkusit, DeliverEat and others.

Food delivery applications is a courier service in which stores, restaurants or third-party

applications delivers food to consumers on demand. These days, orders are executed through

mobile apps, websites or via telephone. Deliveries include cooked dishes as well as groceries

from supermarkets. Other methods of food delivery include catering or wholesale. The first

recorded instance of a meal delivery comes from Italy in 1889. King Umberto and his Queen

Margherita and called Raffaele Esposito, the creator of the Pizza Margherita, to deliver a pizza

to their palace in Naples (Viktor, 2020). Food delivery applications offer food service

customers the ability to search through diverse products and compare costs. Small-scale

restaurants that have lower advertising and marketing abilities can use delivery apps as a

convenient and highly efficient sales and marketing tool (Lee, Sung, & Jeon, Determinants of

Continuous Intention on Food Delivery Apps: Extending UTAUT2 with Information Quality,

2019).

3

This research therefore seeks to analyse on factors influence food delivery applications

usage among students of Politeknik Sultan Salahuddin Abdul Aziz Shah during Movement

Control Order (MCO).

1.3 PROBLEM STATEMENT

Individuals who are busy doing work or assignments at a given time having problems

and lead to the food delivery applications. According to Belanche, Flavián, & Pérez-Rueda

(2020), food delivery applications is perfect for people who are busy in their work life and the

applications suits the lifestyle of the customer such as eating at home and ordering via mobile

phone. They are willing not to go out to buy food. There are some students who are feeling

lazy to buy food. Besides, students will feel wasted time for waiting for food when there are

crowded.

However, during Movement Control Order (MCO), mostly people are likely to buy

their foods through food delivery applications. Because of that, food delivery applications are

intended to fulfil customers needs among students of Politeknik Sultan Salahuddin Abdul Aziz

Shah. Students can get a benefits from using food delivery applications which is the probability

of contracting Coronavirus was low.

Customers can access the website and choose the restaurant according to the real-time

customized using the system provided which is the food delivery service application

(Hendrickson, 2016).

Students also feel bored with the same food sometimes they want to try something

different especially when the food is viral. The visual effects of food will affect the expectations

on how the taste of food and can also affect the real taste (Gayler & Sas, 2017).

4

1.4 RESEARCH OBJECTIVES

The main objectives of this study are as per below:

1.4.1 To examine relationship between social influence with food delivery

applications usage among students of Politeknik Sultan Salahuddin Abdul Aziz

Shah.

1.4.2 To examine relationship between facilitating conditions with food delivery

applications usage among students of Politeknik Sultan Salahuddin Abdul Aziz

Shah.

1.4.3 To examine relationship between habit with food delivery applications usage

among students of Politeknik Sultan Salahuddin Abdul Aziz Shah.

1.5 RESEARCH QUESTIONS

The research question for this study are as per below:

1.5.1 Does social influence has relationship with food delivery applications usage

among students of Politeknik Sultan Salahuddin Abdul Aziz Shah.

1.5.2 Does facilitating conditions has relationship with food delivery applications

usage among students of Politeknik Sultan Salahuddin Abdul Aziz Shah.

1.5.3 Does habit has relationship with food delivery applications usage among

students of Politeknik Sultan Salahuddin Abdul Aziz Shah.

1.6 SCOPE OF RESEARCH

This research is perform on students of Politeknik Sultan Salahuddin Abdul Aziz Shah.

Therefore, this study can find out the factors influence food delivery application usage among

students of Politeknik Sultan Salahuddin Abdul Aziz Shah during Movement Control Order

(MCO). This research will also allow analysis and conclusions to be drawn based on the answer

of the students in the online questionnaire. The study results will help researchers identify the

factors influence food delivery applications usage among students of Politeknik Sultan

Salahuddin Abdul Aziz Shah during Movement Control Order (MCO).

5

1.7 SIGNIFICANT OF RESEARCH

The significant of this study are:

1.7.1 The researchers discover information related to factors influence students using

food delivery applications that have never been explored by others.

1.7.2 The students from Polytechnic, college or university who want to do a research

regarding the factors influence students using food delivery applications can use

this research as a reference.

1.7.3 The society able to know which factors the most influence students to meet their

needs using food delivery applications during Movement Control Order (MCO).

1.8 DEFINITION OF TERM

1.8.1 Pandemic – A pandemic is the worldwide spread of a new disease. An influenza

pandemic occurs when a new influenza virus emerges and spreads around the

world, and most people do not have immunity. Viruses that have caused past

pandemic typically originated from animal influenza viruses (World Health

Organization (WHO), 2010).

1.8.2 COVID-19 – Coronavirus disease 2019 (COVID-19) is defined as illness

caused by a novel coronavirus now called severe acute respiratory syndrome

coronavirus 2 (SARS CoV-2; formerly called 2019-nCoV), which was first

identified amid an outbreak of respiratory illness cases in Wuhan City, Hubei

Province China. It was initially reported to the WHO on December 31, 2019.

On January 30, 2020, the WHO declared the COVID-19 outbreak a global

health emergency. On March 11, 2020, the WHO declared COVID-19 a global

pandemic, its first such designation since declaring H1N1 influenza a pandemic

in 2009 (Cennimo, MD, FAAP, FACP, & AAHIVS, 2020).

1.8.3 Movement Control Order (MCO) – The Movement Control Order refers to

the Prevention and Control of Infectious Diseases (Declaration of Infected Local

Areas) Order 2020 (“PCID Order”) which was issued by Malaysian Prime

Minister, Tan Sri Muhyiddin Yassin on 16.3.2020 under the Prevention and

Control of Infectious Diseases Act 1988 (“PCID Act 1988”), after being

6

satisfied that all States and Federal Territories in Malaysia are threatened with

an epidemic of an infectious disease, namely Covid-19, a life-threatening

microbial infection specified in Part 1 of the First Schedule of PCID Act 1988

(MahWengKwai & Associates , 2020)

1.8.4 Food Delivery Applications – Technological evolution has completely

changed the entire scenario of the restaurant industry. It has uplifted the usage

of online food delivery services and enabled us to order food at the comfort of

our home, compare prices and conveniently access these services. These online

food delivery services are boosting the option of choosing meals from a wide

variety of restaurants with a single tap of our smartphones (Das & Ghose, 2019).

1.8.5 Social Influence – Social influence has been validated as significantly

determining users' intention to use an online-to-offline delivery service (Park,

2019). Social influence as an important variable in Unified Theory of

Acceptance and Use of Technology (UTAUT) has a significant impact on users'

intentions to continue using mobile technologies (Lai & Shi, 2015).

1.8.6 Facilitating Conditions – Facilitating conditions such as resources availability,

skills as well as technical infrastructure could play a significant role towards

digital library use among engineering lecturers. Given that an individual

perceives that using a system will improve his job performance represents

performance expectancy, while availability of technical and organisational

infrastructure required to use a system represents the facilitating conditions;

both performance expectancy and facilitating conditions could be said to play a

critical role and have direct impact on the use of any system (Hamzat &

Mabawonku, 2018)

1.8.7 Habit – According to the Limayem, Hirt, & Cheung (2007), habit is defined as

tendencies that are performed automatically through learning. In addition, habit

is sometimes affected by current environmental conditions or past experiences

and may not be conscious (Hsu, Chang, & Chuang, 2015).

7

1.9 SUMMARY

This chapter contained an introduction to research that researchers want to do about the

factors influence food delivery applications usage among students of Politeknik Sultan

Salahuddin Abdul Aziz Shah during Movement Control Order (MCO). This chapter also

contained the research’s background, problem statement, research objectives, research

questions, scope of research, significant of research as well as definition of operational terms.

In order to provide a clear explanation for the definition of this analysis and develop a

theoretical framework, Chapter 2 will continue the study by reviewing the literature for each

variable in this study.

8

CHAPTER 2: LITERATURE REVIEW

2.1 INTRODUCTION

The factors influence food delivery applications usage among students of Politeknik

Sultan Salahuddin Abdul Aziz Shah during Movement Control Order (MCO) will be discussed

in this chapter. The approach includes some study of the food delivery applications, social

influence, facilitating conditions, habit and students of Polytechnic. The literature review

showed further discussion on the feasibility of using food delivery applications among students

in depth.

Based on the survey held by Russ & Yus (2020), in particular, when the Covid-19

spreads in some countries, especially in China, the online food delivery can contribute to

keeping food quality control stable in the food health and food safety from the Convid-19, with

the “contactless” pickup and delivery services to make the deliver workers and customers safe,

this delivery can also make the food health and quality sustainable in the whole delivery

process.

Service and delivery service it is defined as the act, the process or the actuation those

are provided by the company or individuals. Comparing to the physical goods, the service is

the intangible actions in the economy and the market (Zeithaml, Bitner, & Gremler, 2014).

According to Kotler & Keller (2018), defined services as acts or performances provided by one

party to another.

In conclusion, during Movement Control Order (MCO) factors affect the use of food

delivery application among students of Politeknik Sultan Salahuddin Abdul Aziz Shah is social

influence, facilitating conditions and habit.

2.2 LITERATURE REVIEW

The goal of the literature review is to explore in more detail the factors affecting this

research. Other than that, literature reviews also known as secondary sources, only include

previous research and do not reveal any new or original research information

9

2.2.1 STUDENTS OF POLYTECHNIC

The establishment of Premier Polytechnics officially announced by The Minister of

Ministry of Higher Education during the launching of Polytechnic Transformation Plan on 25

February 2010. The three institutions chosen are Politeknik Sultan Salahuddin Abdul Aziz

Shah in Shah Alam, Selangor, Politeknik Ungku Omar in Ipoh, Perak and Politeknik Johor

Baru, Johor (Richard Lim, 2010).

The premier polytechnic is expected to lead the field of thrust programs (niche area)

and specific technology that can produce quality graduates with entrepreneurship abilities.

Graduates must be trained in entrepreneur skill in order for them to sustain in the respective

industries. Addition to the above, by developing an international reputation and being

preeminent national higher institution in TVET, polytechnic will become the attraction of

higher education choice for students locally and internationally (Shahul Hamid, 2010).

There is 4,730 active students of Politeknik Sultan Salahuddin Abdul Aziz Shah (Portal

Rasmi, 2020). Therefore, students of trade department Politeknik Sultan Salahuddin Abdul

Aziz Shah were respondents in this research. This study was focused on polytechnic students

who are aged between 18 to 25 years old.

10

2.2.2 FOOD DELIVERY APPLICATIONS

Jacob, Sreedharan & Sreena.K (2019), stated that online food delivery mobile

applications has become popular over these years. There are wide varieties of restaurants now

delivering online services at best offers and reasonable prices. The online food ordering system

sets up a food menu online with the help of mobile applications like Grab Food, Food Panda

and Dah Makan.

Das & Ghose (2019), pointed that the technological evolution has completely changed

the entire scenario of the restaurants industry. It has uplifted the usage of online food delivery

services and enabled us to order food at the comfort of our home, compare prices and

conveniently access these services. These online food delivery services are boosting the option

of choosing meals from a wide variety of restaurants with a single tap of our smartphones.

However, using these applications will provide tracking system where the customers

become more acquainted with each progression of delivering. In addition, these applications

also provide a feedbacks and recommendations, rate the food item and mode of delivering

(Jacob et. al, 2019). This will facilitate the affairs of students Politeknik Sultan Salahuddin

Abdul Aziz Shah in tracking their orders during Movement Control Order (MCO) because they

cannot go out regarding “stay at home” orders.

In conclusion, food delivery applications which is very popular nowadays giving

advantages to customers especially students because they can order their food at home without

having to go out due to the order of “stay at home” during Movement Control Order (MCO).

11

2.2.3 SOCIAL INFLUENCE

Social influence has been validated as significantly determining users' intention to use

an online-to-offline delivery service (Roh & Park, 2019). Social influence as an important

variable in Unified Theory of Acceptance and Use of Technology (UTAUT) has a significant

impact on users' intentions to continue using mobile technologies (Lai & Shi, 2015). This angle

has been supported in various aspects, such as mobile social network sites (Zhou & Li, 2014),

shopping apps (Chopdar & Sivakumar, 2018) and mobile payment systems (Zhu, Lan, &

Chang, 2017).

Furthermore, social influence not only directly determines users' continuance intention,

but also indirectly formulates users' intention to continuously use mobile technology by

affecting their satisfaction (Hsiao, Chang, & Tang, 2016). Veljko Marinković, Đorđević, &

Zoran Kalinić (2020), revised Unified Theory of Acceptance and Use of Technology (UTAUT)

to confirm that social influence has a significant effect on users' satisfaction towards

continuance intention of using mobile technology.

Social influence or subjective norms refers to the degree of individuals believe that

relevant others would approve of certain behaviour (Du, Zhu, Lv, & Sun, 2012).

Due to the social influence, people who are more important and close can be one of the

factors influence food delivery applications usage among the students of Politeknik Sultan

Salahuddin Abdul Aziz Shah during Movement Control Order (MCO). Besides that, the people

who influence someone behaviour can also influence the students to using the food delivery

applications during the Movement Control Order (MCO). Lastly, one factors that influence

customers perception on food delivery application usage among students of Politeknik Sultan

Salahuddin Abdul Aziz Shah during Movement Control Order (MCO) is people whose

opinions that the students value such as their parents, family and others.

12

2.2.4 FACILITATING CONDITIONS

Facilitating conditions such as resources availability, skills as well as technical

infrastructure could play a significant role towards digital library use among engineering

lecturers. Given that an individual perceives that using a system will improve his job

performance represents performance expectancy, while availability of technical and

organisational infrastructure required to use a system represents the facilitating conditions; both

performance expectancy and facilitating conditions could be said to play a critical role and

have direct impact on the use of any system (Hamzat et. al, 2018).

According to Liao & Cheung (2008), by performing online banking, transactions can

be performed without have to walk in personally over the counter. Meanwhile, 50% of

respondents in the study by Singhal & Padhmanabhan (2008) agreed that internet banking is

convenient and flexible ways of banking and it also have various transaction related benefits.

Due to facilitating conditions, the students of Politeknik Sultan Salahuddin Abdul Aziz

Shah have the knowledge necessary to use food delivery applications for purchasing their foods

during Movement Control Order (MCO). Mostly students of Politeknik Sultan Salahuddin

Abdul Aziz Shah feel more comfortable using food delivery applications for purchasing food

at their favourite eateries during Movement Control Order (MCO) because it is the most easier

and safer.

13

2.2.5 HABIT

The term ‘habit’ is widely used to predict and explain behaviour. The definition of

'habit' is an implied disorder and is not related to theory. Habit is the context and implicit

response that develops through the learning of repetitive rewards (Wood & Runger, 2016).

Habit also a modern personality of psychology and is largely a social loss (Wood, 2017).

Consumer behaviour is a situation in which the customer, groups or organizations

select, purchase, use, and differentiate the ideas, goods, and services for their needs and wants.

It refers to consumer actions in the market and the basis of one’s actions (Ayush, Rubi,

Manisha, Kumari Vishaka, & Sonam, 2019).

Population consumption habits are changed and transformation is rushing from

traditional business to online business to survive the epidemic of maintaining business despite

the negative influence of Covid-19 pandemic throughout the Movement Control Order (MCO).

From the end of February 2020 to the beginning of March 2020 there were 71.7% of the 15,263

participants using the food delivery applications and 41.6% of the population prefers to use

online to offline services for buy daily supplies during Covid-19 pandemic in China. The food

delivery applications become an increasingly popular and most useful platform for the food

service industry throughout covid-19 as well as growing steadily. Customers can enjoy food at

home and at the same time be able to protect themselves from the Covid-19 pandemic which

also formulates new consumption habits for sustainable use (Zhao et. al, 2020).

Based on Prabowo & Nugroho (2018), there are various food delivery services through

internet and mobile applications as food delivery services are growing. Due to the busy

schedule and congested traffic causing people to choose to order food using smartphones and

delivered immediately and this become trend nowadays.

In a nutshell, there are variety of habit among customers. Based on the research, most

habit that customers have is they don’t have time to cook because of their busyness.

14

2.3 HYPOTHESES OF THE STUDY

2.3.1 SOCIAL INFLUENCE

According to the Singh & Matsui (2017), they found that there is a significant

relationship between social influence and food delivery applications usage. This is because

they stated if socially connected people who are using newer web technologies for shopping,

then this could be a factor of influence for intention to use. Based on the research by Lee, Sung

& Jeon (2019) also stated that social influence has been validated as positively influencing

users’ behavioural intentions for new technologies, products and services. However, the more

favourable the social influence of a behaviour, the stronger an individual’s intention to perform

it (Bendegul, Faizan, Anil, & Bulent Ozturk, 2018). Regarding independent variable for social

influence, the following is the proposed hypotheses:

H1: There is a significant relationship between social influence and food delivery applications

usage.

2.3.2 FACILITATING CONDITIONS

According to the Venkatesh, Thong & Xu (2012), they found the significant

relationship between facilitating conditions and food delivery application usage. This is

because they stated that users who deem facilitating conditions to be adequate are less averse

to using a new service, thus strengthening their use intentions. However, based on the research

of Lakhal, Khechine & Pascot (2013) verified facilitating conditions as a significant

determinants of students’ intentions to use. In another study, Unified Theory of Acceptance

and Use of Technology (UTAUT) did not consider the relationship between facilitating

conditions and usage intention, but, due to their important role, several previous studies have

tested and confirmed the effect of facilitating conditions on acceptance and usage of systems

(Ali, Pradeep & Kashif, 2016). Regarding independent variable for facilitating conditions, the

following is the proposed hypotheses:

H2: There is a significant relationship between facilitating conditions and food delivery

applications usage.

15

2.3.3 HABIT

According to the Singh & Matsui (2017) mentioned habitual users of online shopping

will tend to browse online stores as part of their natural behavior. Habit can influence on both

intention to use and use behavior. It showed this study found the significant relationship

between habit and food delivery applications usage. In another study, habit is sometimes

affected by current environmental conditions or past experiences and not be concious (Hsu,

Chang & Chuang, 2015). Based on the research of Venkatesh, Thong & Xu (2012) stated that

prior experience use is a prerequisite for habit to influence the use and that habit was a key

factor in future acceptance. Regarding independent variable for habit, the following is the

proposed hypotheses:

H3: There is a significant relationship between habit and food delivery applications usage.

16

2.4 THEORATICAL FRAMEWORK

Figure 1: Research Framework

Sources: (Lee, Sung, & Jeon, Determinants of Continuous Intention on Food Delivery Apps:

Extending UTAUT2 with Information Quality, 2019)

The purpose of this research is to study the factors influence food delivery applications

usage among students of Politeknik Sultan Salahuddin Abdul Aziz Shah during Movement

Control Order (MCO). There are three independent variables (IV) chosen by the researcher,

which are social influence, facilitating conditions and habit while the dependent variable (DV)

is factors influence food delivery applications usage.

2.5 SUMMARY

Basically, in this chapter provide more comprehensive information about food delivery

applications, social influence, facilitating conditions, habit and our respondents which is

students of Polytechnic. However, in this chapter also tells about the hypotheses regarding the

relationship between each independent variable (IV) and food delivery applications usage.

Habit

(IV)

Facilitating Conditions

(IV)

Social Influence

(IV)

Food Delivery

Applications

(DV)

H1

H2

H3

17

CHAPTER 3: RESEARCH METHODOLOGY

3.1 INTRODUCTION

Methodology is research where certain researchers should take appropriate measures to

examine the problem of research and certain methods are used to classify, select, process and

evaluate data. To understand the issues, all the approaches that are used will be used. It is

intended for the reader to estimate the figure and to be able to trust it. The research methodology

are divided into two sections which are how was the data collected or created? And, how was

it investigated? This research is done by using quantitative research that allows researchers to

identify social influence, facilitating conditions and habit with food delivery applications usage

among students of Politeknik Sultan Salahuddin Abdul Aziz Shah during Movement Control

Order (MCO). This chapter included the contents which are the methods that are chosen to do

the research design, methods on data collection, how the sample was selected, what the

instrument used in research, what the techniques used in sampling data and analysis such as

how the questionnaire was developed.

3.2 RESEARCH DESIGN

The summary of the defining framework, plan or strategy analysis procedure is shown

in the design of the research. The content of this chapter will cover the research approach,

sampling method, how to collect data, technique for processing and analysing data and report

writing.

This research would be conducted by using a quantitative approach. The survey

instrument was customized to identify on social influence, facilitating conditions and habit with

food delivery applications usage among students of Politeknik Sultan Salahuddin Abdul Aziz

Shah during Movement Control Order (MCO).

A sample of 357 students was selected randomly using Krejcie and Morgan Table

(KENPRO, 2012) based on the population of average students that use food delivery

applications which is 4730 students in Politeknik Sultan Salahuddin Abdul Aziz Shah (Portal

Rasmi, 2020). This research was conducted to get the data through questionnaire that had been

give out to the students of Politeknik Sultan Salahuddin Abdul Aziz Shah. Questionnaires were

the popular and most productive method to collect data used by researchers.

18

3.3 DATA COLLECTION METHOD

Data collection is the process of gathering and measuring information on variables of

interest, in an established systematic fashion that enables one to answer stated research

questions, test hypotheses, and evaluate outcomes. The data collection component of research

is common to all fields of study including physical and social sciences, humanities, business,

etc (Syed Muhammad Sajjad, 2016).

Data collection methods can be divided into two categories which is primary data and

secondary data. Primary data consist of information collected for specific purposes and primary

data is also collected by surveys and analysis. Secondary data consist of information that

already exists that has been gathered for some purposes.

3.3.1 PRIMARY DATA

Data that has been collected from first-hand-experience is known as primary data.

Primary data has not been published yet and is more reliable, authentic and objective. Primary

data has not been changed or altered by human beings; therefore its validity is greater than

secondary data. Sources for primary data are limited and at times it becomes difficult to obtain

data from primary source because of either scarcity of population or lack of cooperation.

Following are some of the sources of primary data (Syed Muhammad Sajjad, 2016).

In this research, researcher has conducted a survey with students of Politeknik Sultan

Salahuddin Abdul Aziz Shah and distribute questionnaire to them using Google Form. The

questionnaire was distributed to the students through and it is includes the questions about their

general information and factors influence food delivery applications usage among students of

Politeknik Sultan Salahuddin Abdul Aziz Shah.

19

3.3.2 SECONDARY DATA

Data collected from a source that has already been published in any form is called as

secondary data. The review of literature in any research is based on secondary data. It is

collected by someone else for some other purpose but being utilized by the researcher for

another purpose. Secondary data is essential, since it is impossible to conduct a new survey

that can adequately capture past change and/or developments (Syed Muhammad Sajjad, 2016).

Researchers use the previous journal in this research as a reference to guide when doing

all the research.

3.4 RESEARCH INSTRUMENT

Research instrument involves questionnaire design, pilot test, and construct

measurement that discusses the instrument that will be used to measure on factors that influence

food delivery applications usage among students of Politeknik Sultan Salahuddin Abdul Aziz

Shah during Movement Control Order (MCO).

The structure of questionnaire was designed in English language because it is more

appropriate to communicate with our respondents. Moreover, the questionnaire was divided

into two parts. Section A is about demographic profile of respondents and Section B is about

dependent and independent variable questions.

In Section A, the questions help to identify the profiles of respondents such as gender,

age, marital status, source of income and course of study. Other than that, the questions in

Section A also asked to gain general information of respondents.

In Section B, much deeper and precise questions were asked regarding their social

influence, facilitating conditions and habit on food delivery applications. To identify, the

questions asked using the Likert Scale are as follow:

20

Section A: Demographic Profile

Please indicate (✔) in the appropriate information about yourself. Each question should only

have ONE answer.

1. Gender

Male Female

2. Age

18 and below 19 – 22 23 and above

3. Marital status

Single Married

4. Income

Below RM 400 RM 401 – RM 800

RM 801 – RM 1,200 RM 1,201 and above

5. Course of study

Business Non-business

6. Do you own a smartphone

Yes No

7. Have you ever downloaded applications for your mobile device?

Yes No

8. Do you know about Food Delivery Applications?

Yes No

9. Which food delivery applications have you downloaded?

Food Panda Dah Makan

Grab Food Others:_________________

21

Section B: Independent and Dependent Variables

Please tick (✔) your answer to each statement using Likert scale.

Table 3.1 Food Delivery Applications (Dependent Variable)

No. Questions Strongly

disagree Disagree Neutral Agree

Strongly

agree

1. I am familiar with food

delivery applications

2.

I know about food delivery

applications through

advertisement on social

media.

3.

I do realize about the

existence of food delivery

applications until now.

4. I do have an experience of

food delivery applications.

5. I have heard about food

delivery applications.

22

Table 3.2 Social Influence (1st Independent Variable)



Strongly

agree

1.

People who are important to

me think that I should use

food delivery applications for

purchasing foods.

2.

People who influence my

behaviour think that I should

use food delivery applications

for purchasing foods.

3.

People whose opinions I value

prefer that I use food delivery

applications for purchasing

foods.

Source: (Lee, Sung, & Jeon, Determinants of Continuous Intention on Food Delivery Apps:


23

Table 3.3 Facilitating Conditions (2nd Independent Variable)



Strongly

agree

1.

I have the knowledge

necessary to use food delivery


foods.

2.

I feel comfortable using food

delivery applications for

purchasing foods.



24

Table 3.4 Habit (4th Independent Variable)



Strongly

agree

1.

Purchasing foods through

food delivery applications is

almost like a habit for me.

2.

I am addicted to using food

delivery applications for the

purchase of foods.

3.

I must use food delivery


foods.

4.

Using food delivery


foods has become natural to

me.



25

3.5 SAMPLING TECHNIQUE

According to Taherdoost (2016), the first stage in the sampling process is to clearly

define target population. A sampling frame is a list of the actual cases from which sample will

be drawn. The sampling frame must be representative of the population. Prior to examining the

various types of sampling method, it is worth noting what is meant by sampling, along with

reasons why researchers are likely to select a sample. Taking a subset from chosen sampling

frame or entire population is called sampling. Sampling can be used to make inference about a

population or to make generalization in relation to existing theory. In essence, this depends on

choice of sampling technique.

Sampling technique are one of the important parts of social research. In order to answer

the research questions, researches should be able to collect data by use the sampling technique

that specially made for information collection. Therefore, researchers use samples when

collecting data to answer problems or research questions.

A related idea of integrating probability and non-probability samples is also explored

in Sakshaug, Wis´niowski, Ruiz, & Blom (2019) who describe a simulation-based approach

rather than the simple and direct analytic derivations presented in this article. Multivariate-

estimates (e.g., regression coefficients), on the other hand, tend to be less susceptible to

discrepancies between probability and non-probability samples (Ansolabehere, S., & Rivers,

2013). According to Fahimi, Barlas, Gross, & Thomas (2014), propose a method they coin

“blended calibration,” where a probability sample weighted to known population totals is

combined with a counterweight non-probability sample, and the combined sample is calibrated

to differentiated variables in the probability-only sample.

In this research, simple random sampling was chosen. Simple random sampling takes

a small, random portion of the entire population to represent the entire data set, where each

member has an equal probability of being chosen (Adam, 2020). However, the population must

be homogenous i.e. every element contains same kind of characteristics that meets the

described criteria of target population (Alvi, 2016).

All targeted respondents will be ask to read and answer the questionnaire specially

made online in 7 - 10 minutes to complete it.

26

3.6 DATA ANALYSIS METHOD

When something is possible to collect all the data, the data will be turned into valuable

analysis knowledge. Data analysis is the process of systematically applying statistical or logical

technique to describe and illustrate, condense and recap and analyse data. Successfully

gathered data was analysed to assess how the sample for this study reacts to the items under

investigations. Using statistical summary tables and charts, the results of the analysis could

then be displayed.

3.6.1 DESCRIPTIVE ANALYSIS

Descriptive statistics are data analysis by percentage, frequency and by using Measure

of central tendency (MCT) - mean, mode and median. In descriptive statistics, the type of data

analysis often involves in variety analysis using only one variable.

According to Ethridge & D.E. (2004), descriptive research can be explained as a

statement of affairs as they are at present with the researcher having no control over variable.

Moreover, “descriptive studies may be characterized as simply the attempt to determine,

describe or identify what is, while analytic research attempts to establish why it is that way or

how it came to be.

According to Fox & Bayat (2007), descriptive research is “aimed at casting light on

current issues or problems through a process of data collection that enables them to describe

the situation more completely than was possible without employing this method. In its essence,

descriptive studies are used to describe various aspects of the phenomenon. In its popular

format, descriptive research is used to describe characteristics and/or behaviour of sample

population.

Frequency distribution is a mathematical division with the purpose of obtaining a count

of the number of responses connected with different values if one variable and to express these

counts in term of percentage. The purpose of frequency is to demonstrate the values such as

numbers and percentages for different categories of a single categorical variable.

27

3.7 SCALE MEASUREMENT

3.7.1 RELIABILITY TEST

Reliability is concerns the extent to which a measurement of a phenomenon give stable

and consist result (Carmines & Zeller, 1979). According to Huck (2007), testing for reliability

is important as it refers to the consistency across the parts of a measuring instrument. The most

commonly used internal consistency measure is the Cronbach Alpha coefficient. It is viewed

as the most appropriate measure of reliability when making use of Likert scales (Whitley, 2002

& Robinson, 2009).

According to Bruin (2011), Cronbach’s alpha is a measure of internal consistency, that

is, how closely related a set of items are as a group. A “high” value for alpha does not imply

that the measure is undimensional. Technically speaking, Cronbach’s alpha is not a statistical

test – it is a coefficient of reliability (or consistency).

Based on the Table 3.5, it showed the range of reliability and its coefficient of

Cronbach’s Alpha as a guide to determine the results of pilot test.

Table 3.5 Range of reliability and its coefficient of Cronbach’s alpha

No. Coefficient of Cronbach’s Alpha Reliability Level

1. More than 0.90 Excellent

2. 0.80 – 0.89 Good

3. 0.70 – 0.79 Acceptable

4. 0.60 – 0.69 Questionable

5. 0.50 – 0.59 Poor

6. Less than 0.59 Unacceptable

Source: Adapted from Khairul Zahreen, Syuhaida, & Abd Latif (2018)

28

3.7.2 PILOT TEST

Pilot test are implemented to determine whether problems exist that need to be

addressed prior to putting the production survey in the field (Lavrakas, 2008). Based on the

Table 3.5 above, if the reliability scale was greater than 0.70, it means the questionnaires are

good and reliable to use. But if the reliability scale showed less than 0.70, the questionnaire

were unreliable to be used in this research. Cronbach’s alpha test may be used in conditions

other than the production or testing of the questionnaire, there is little literature on its use in

those conditions (Mohamad Adam, Evi Diana, & Nur Akmal, 2018).

For this research, about 31 out of 357 respondents were distributed the questionnaires

for the pilot test requirements among students of Politeknik Sultan Salahuddin Abdul Aziz

Shah. The findings of the reliability test have been presented in the Table 3.6 below. Since

the Cronbach's Alpha valued more than 0.7 each, each test was significant.

Table 3.6 Reliability Test for 31 Respondents

Variables Items Cronbach’s Alpha

Dependent Food Delivery Applications 5 .827

Independent Social Influence 3 .804

Facilitating Conditions 2 .916

Habit 4 .930

After constructing for each variable, the outcome of the reliability test showed that the

habit is the highest, which is 0.930 and followed by facilitating conditions, which is 0.916.

Next is food delivery applications which is 0.827 and the last one is social influence which is

0.804. Based on the Alpha Coefficient Range Strength of Association, all of these variable

exceed 0.7 which is acceptable.

29

3.8 SUMMARY

Finally, it may concluded that research methodology have been used in gathering,

reviewing and simplifying data. This chapter given the summary about the methodology which

research design and research instrument is decided, data collection methods and data analysis

method are introduced, sampling technique and scale measurement are clarified. However, in

the earlier component of this chapter were mentioned about target population, sampling frame

and sampling size.

30

CHAPTER 4: ANALYSIS AND RESULT

4.1 INTRODUCTION

In this chapter, each results obtained from the questionnaire used for the survey

respondent’s data would be investigated. Data that researchers collected from 357 respondents

were investigated using Statistical Package for the Society Sciences (SPSS) Version 22

software program. Furthermore, elements that would be covered in this chapter include

demographic profile and descriptive analysis (food delivery applications, social influence,

facilitating conditions and habit). The results would kindly be presented in charts and tables.

Lastly, this chapter would be concluded with a summary on research findings.

4.2 DEMOGRAPHY PROFILE OF RESPONDENTS

A total of 357 of questionnaire were answered by the students of Politeknik Sultan

Salahuddin Abdul Aziz Shah through Google Form that researchers has created to conduct the

survey. From the amount of questionnaire answered, it has been answered excellently.

For demographic data, the questions were asked to the respondents such as gender, age,

marital status, income and course of study. All the demographic data has been analysed using

Statistical Package for the Society Sciences (SPSS) Version 22.

The total of all respondents obtained from the questionnaires through Google Form

were 357 respondents. By referring the Table 4.1, it showed the majority of the respondents

were female with 228 respondents (63.9%) and male were 129 respondents (36.1%).

The range age of the respondents was high at 19 – 22 years old comprised of 316

respondents (88.5%). Next, 18 years old and below with 34 respondents (9.5%) while 23 years

old and above with 7 respondents (2%).

For marital status, majority of the respondents (99.7%) are single and 1 of the

respondents (0.3%) is married.

As for income, more than half respondents which are 245 respondents (68.6%) are

below RM400. Other than that, 66 respondents (18.5%) are having a monthly income ranging

from RM401 – RM800 while 38 respondents (10.6%) having monthly income from RM801 –

31

RM 1,200. Only 8 respondents (2.2%) have monthly income from RM 1, 201 and above.

Last but not least, 199 respondents (55.7%) which are more than half respondents from

business students and 158 respondents (44.3%) are non-business students.

The profile of the respondents is shown in Table 4.1 and Appendix C.

Table 4.1 Demographic Profile

Respondent’s Demographic Frequency Percentage (%)

Gender Male 129 36.1

Female 228 63.9

Age 18 and below 34 9.5

19 – 22 years 316 88.5

23 and above 7 2.0

Marital status Single 356 99.7

Married 1 0.3

Income Below RM400 245 68.6

RM401 – RM800 66 18.5

RM801 – RM1,200 38 10.6

RM1,2001 and above 8 2.2

Course of study Business 199 55.7

Non-business 158 44.3

Source: Developed from the research

32

As shown in Table 4.2, all of the respondents owned a smartphone. Each of them has

downloaded applications in their smartphones. All the respondents know about food delivery

applications.

Most of the respondents had downloaded Food Panda applications with 56.9% which

is 203. Second highest in downloaded food delivery applications is Grab Food with 27.2%, 97

respondents. Third highest is Dah Makan with 49 at 13.7%. The results showed some

respondents downloaded BungkusIt applications with 1.1% which are 4.

Table 4.2 General Information

General Frequency (N) Percentage (%)

Do you own a smartphone? Yes 357 100.0

No 0 0

Have you ever downloaded Yes 357 100.0

applications for your mobile device? No 0 0

Do you know about Food Delivery Yes 357 100.0

Applications? No 0 0

Which food delivery applications Food Panda 203 56.9

have you downloaded? Grab Food 97 27.2

Dah Makan 49 13.7

BungkusIt 4 1.1

Others 4 1.1

Source: Developed from the research

33

4.3 GOODNESS MEASURE

4.3.1 DESCRIPTIVE ANALYSIS

Table 4.3 includes a summary of the descriptive analysis of the variables. In the 5-point

Likert scale, all variables were measured with 5 being strongly agreed.

Table 4.3 Overall Descriptive Analysis of the Variables

Mean Standard Deviation

Food Delivery Applications 4.46 .560

Social Influence 3.82 .783

Facilitating Conditions 4.36 .745

Habit 3.50 .964

4.4 RESEARCH FINDINGS

4.4.1 STATISTICAL SUMMARY

In order to determine the 'quality' of each decision variable, statistical measurements

were measured from deterministic sampling of available methods (Sun, Li, & Ernst, 2019).

That said however, the mean field theory is based on the central boundary theorem with the

parameters generated in a manner with finite variances (Karakida, Akaho, & Amari, 2019)

while standard deviation used to analyse a dataset's distribution according to the mean

(Hargrave, 2020)

34

Table 4.4 Food Delivery Applications

Code Statement Mean Standard Deviation

FDA 1 I am familiar with food delivery applications 4.38 .758

FDA 2 I know about food delivery applications through

advertisement on social media.

4.33 .784

FDA 3 I do realize about the existence of food delivery

applications until now.

4.56 .654

FDA 4 I do have an experience of food delivery applications. 4.37 .827

FDA 5 I have heard about food delivery applications. 4.64 .547

Based on Table 4.4, for food delivery applications, FDA 5 (I have heard about food

delivery applications) indicate the highest mean score with 4.64 and standard deviation at

0.547. On the other side, FDA 2 (I know about food delivery applications through

advertisements on social media) indicate the lowest mean score with 4.33 and standard

deviation at 0.784.

35

Table 4.5 Social Influence


SI 1 People who are important to me think that I should

use food delivery applications for purchasing foods.

4.06 .916

SI 2 People who influence my behaviour think that I

should use food delivery applications for purchasing

foods.

3.66 .915

SI 3 People whose opinions I value prefer that I use food

delivery applications for purchasing foods.

3.75 .880

As for the social influence in Table 4.5, SI 1 (People who are important to me think that

I should use food delivery applications for purchasing foods) indicate the highest mean with

4.06 and standard deviation 0.916 while SI 2 (People who influence my behaviour think that I

should use food delivery applications for purchasing foods) indicate the lowest mean with 3.66

and standard deviation at 0.915.

36

Table 4.6 Facilitating Conditions


FC 1 I have the knowledge necessary to use food delivery

applications for purchasing foods.

4.28 .841

FC 2 I feel comfortable using food delivery applications


4.45 .750

Based on facilitating conditions from Table 4.6, FC 2 (I feel comfortable using food

delivery applications for purchasing foods) indicate the highest mean with 4.45 and standard

deviation at 0.750 and the lowest mean with 4.28 and standard deviation at 0.841 is FC 1 (I

have the knowledge necessary to use food delivery applications for purchasing foods).

37

Table 4.7 Habit


HABIT 1 Purchasing foods through food delivery applications is


3.18 1.161

HABIT 2 I am addicted to using food delivery applications for

the purchase of foods.

3.32 1.190

HABIT 3 I must use food delivery applications for purchasing

foods.

3.69 1.114

HABIT 4 Using food delivery applications for purchasing foods

has become natural to me.

3.79 1.103

Last but not least, habit for Table 4.7, HABIT 4 (Using food delivery applications for

purchasing foods has become natural to me) indicate the highest mean with 3.79 and standard

deviation at 1.103 while HABIT 1 (Purchasing foods through food delivery applications is

almost like a habit for me) indicate the lowest mean with 3.18 and standard deviation at 1.161.

38

4.5 HYPOTHESES TESTING

4.5.1 CORRELATION COEFFICIENTS RANGE

In order to evaluate the inter-correlations among all the research variables, Pearson

Product-Moment Correlation was used. Summaries of the results are given in Table 4.8 and

Appendix F.

Table 4.8 Pearson Correlation Coefficient (r) Strengths

Strength of Correlation Range of Absolute Correlation

Coefficient (r)

0.8 – 1.0 Very strong

0.6 – 0.79 Strong

0.4 – 0.59 Moderate

0.2 – 0.39 Weak

0 – 0.19 Very weak

Source: (Liang, et al., 2019)

4.5.2 CORRELATION ANALYSIS

Table 4.9 Pearson’s Correlation Coefficients of the Variables

Food Delivery

Applications

Social

Influence

Facilitating

Conditions Habit

Food Delivery Pearson Correlation 1

Applications Sig. (2-tailed)

N 357

Social Pearson Correlation .441** 1

Influence Sig. (2-tailed) .000

N 357 357

Facilitating Pearson Correlation .657** .436** 1

Conditions Sig. (2-tailed) .000 .000

N 357 357 357

Habit Pearson Correlation .417** .366** .359** 1

Sig. (2-tailed) .000 .000 .000

N 357 357 357 357

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

39

4.5.2.1 Relationship between food delivery applications and social

influence

Based on the Table 4.8, the result for the correlation coefficient of the pair between

food delivery applications and social influence was moderate strength which is r = 0.441 (p-

value = 0.000) (p < 0.005). The correlation coefficient value (r = 0.441) stated that there was a

positive relationship between this two variables. The results thus indicated that there was a

significant relationship between food delivery applications and social influence with a

significant value of 0.000.

4.5.2.2 Relationship between food delivery applications and facilitating

conditions


food delivery applications and facilitating conditions was moderate and the highest strength

which is r = 0.657 (p-value = 0.000) (p < 0.005). The correlation coefficient value (r = 0.657)

showed that there was a positive relationship between this two variables. The results thus

specified that there was a significant relationship between food delivery applications and

facilitating conditions with a significant value of 0.000.

4.5.2.3 Relationship between food delivery applications and habit


food delivery applications and habit was moderate and the lowest strength which is r = 0.417

(p-value = 0.000) (p < 0.005). The correlation coefficient value (r = 0.417) revealed that there

was a positive relationship between this two variables. The results thus stipulated that there

was a significant relationship between food delivery applications and habit with a significant

value of 0.000.

40

4.6 SUMMARY

In conclusion, the purpose of this chapter was to present the analyses and results

obtained by data collection using questionnaires given to the respondents. Not just that, all

frameworks were already tested for reliability. The use of food delivery applications among

learners can be seen in this chapter.

41

CHAPTER 5: DISCUSSION AND CONCLUSION

5.1 INTRODUCTION

This chapter will include a summary of the main results by listing out the recapitulation

of the report, providing a detailed conclusion for the descriptive research of Chapter 4, and

providing suggestions for future research.

5.2 RECAPITULATION OF THE STUDY

This study aims to find out the extent to which food delivery applications help its users

to obtain food through the food delivery applications available during the period of Movement

Control Order (MCO). In order to substantiate the research problem, three Independent

Variable - Social Influence, Facilitating Conditions and Habit. The findings of the study will

eventually answer the following questions.

1) Does social influence affects food delivery applications usage among students of

Politeknik Sultan Salahuddin Abdul Aziz Shah?

2) Does facilitating conditions affects food delivery applications usage among students of

Politeknik Sultan Salahuddin Abdul Aziz Shah?

3) Does habit affects food delivery applications usage among students of Politeknik Sultan

Salahuddin Abdul Aziz Shah?

There were several hypotheses developed to test the relationship between the

independents variables and the dependent variable. The first set of hypotheses was developed

to identify the relationship between factors influencing which consist of the social influence,

facilitating conditions and habit in the use of food delivery applications during the period of

Movement Control Order (MCO).

42

5.2.1 DISCUSSION OF MAJOR FINDINGS

The study has shown that social influence has a strongest positive relationship with food

delivery applications perceived ease of use. Social influence was the most salient determinant

of perceived ease of use. This is in line with the research conducted by Park (2019), Lai & Shi

(2015), Hsiao, Chang & Tang (2015), Du, Zhu, LV & Sun (2012). Social influence has been

validated as significantly determining users’ intentions to use an online-to-offline delivery

service. Social influence as an important variable in UTAUT has a significant impact on users’

intentions to continue using mobile technologies. Social influence not only directly determines

users’ continuance intention, but also indirectly formulates users’ intention to continuously use

mobile technology by affecting their satisfaction. Social influence or subjective norms refers

to the degree of individuals believe that relevant others would approve of certain behavior.

Facilitating conditions also has a strong positive relationship with food delivery

applications perceived ease of use. Although 100% of the respondent had a smart phone, the

respondents think that more facilitating resources like smart phone and network connection

will be a key factor in influencing ease of using food delivery applications. According to Liao

& Cheung (2018), by performing online banking, transactions can be performed without have

to walk in personally over the counter. Meanwhile, 50% of respondents in the study by Divya

& V, (2008) agreed that internet banking is convenient and flexible ways of banking and it also

have various transaction related benefits.

Habit also has a strong positive relationship with food delivery applications perceived

ease of use. This is in line with the research conducted by Zhao & Bacao, (2020). Population

consumption habit are changed and transformation is rushing from traditional business to

online business to survive the epidemic of maintaining business despite the negative influence

of Covid-19 pandemic throughout the Movement Control Order (MCO). From the end of

February to the beginning of March 2020 there were 71.7% of the 15,263 participants using

food delivery applications and 41.6% of the population prefer to use online-to-offline services

for buy daily supplies during Covid-19 pandemic in China. The food delivery applications

become an increasingly popular and most useful platform for the food service industry

throughout Covid-19 as well as growing steadily. Customers can enjoy food at home and at the

same time be able to protect themselves from the Covid-19 pandemic which also formulates

new consumption habit for sustainable use.

43

5.3 RECOMMENDATION

5.3.1 RECOMMENDATION FOR FUTURE RESEARCH

This research only discussed and study briefly without much deeper study as finding

factors that would influence food delivery applications usage during Movement Control Order

(MCO). Therefore, hopefully that this research could be a benefit for future research on

improving the model by incorporating other relevant dependent and independent variables

based on new findings from latest literature at the time.

Although it might take a longer time, it would allow the researchers to get a better

understanding and acknowledgement regarding all factors that might be included. Thus, the

research would be provided with wider perspectives.

However, future research could help expand this research to include the effect and

experience on the food delivery applications usage during Movement Control Order (MCO).

This will help for a better analysis.

Last but surely not the least, hopefully this research could be a help for any others food

delivery applications to make a further research in future or a reference to make a better service.

44

5.3.2 RECOMMENDATION FOR FOOD DELIVERY COMPANY AND

STUDENTS

Based on the findings, analysis and conclusion done in this research, there were a few

recommendations could be considered. Company of Food delivery should make a wider

advertisement such as on newspaper, television and any others social media. Despite of having

a high percentage of user acknowledgement towards food delivery applications among students

of Politeknik Sultan Salahuddin Abdul Aziz Shah during Movement Control Order (MCO),

does not mean it is the same situation in any other polytechnic students.

Next, company of Food Delivery should add on more features or service that could ease

users and attract them all at once. Combine with all food delivery providers such as Grab Food,

Food Panda, Dah Makan, BungkusIt and others could be one of the ways to add on more

features or services in one applications. Also, food delivery applications should provide guides

and information for students who just get to know about the food delivery applications during

Movement Control Order (MCO). This could help them to get a better understanding and be

aware of the benefits and services that food delivery applications could provide.

Moreover, during the time of emergency this applications could help the students of

Politeknik Sultan Salahuddin Abdul Aziz Shah in so many ways during Movement Control

Order (MCO). As of during this research was being analysed, a virus disease called Covid-19

that was widely spreading has becoming a problem for all people around the globe. For the

students of Politeknik Sultan Salahuddin Abdul Aziz Shah, going out from their home even for

a moment could be risky and worrying as they might get infected by the virus as the infected

cases were rapidly increasing. This includes going out to buy foods. Thus, food delivery

applications play a crucial role in helping and easing most of the students. They would not have

the need to go out as they can do so many things even by staying home. For example, they can

just order their foods through food delivery applications on their mobile phones.

45

5.4 SUMMARY

The objectives were achieved based on the results and discussions of the study. The

researcher found that the factors influence food delivery applications usage among students of

Politeknik Sultan Salahuddin Abdul Aziz Shah were indeed significant.

46

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52

APPENDIX A: 31 SET OF PILOT TEST

Food Delivery Applications

Reliability Statistics

Cronbach's

Alpha

Cronbach's Alpha Based on

Standardized Items N of Items

.827 .842 5

Social Influence


Cronbach's

Alpha



.804 .811 3



Cronbach's

Alpha



.916 .916 2

Habit


Cronbach's

Alpha



.930 .931 4

53

APPENDIX B: QUESTIONNAIRE

TITLE: THE FACTORS INFLUENCE FOOD DELIVERY APPLICATIONS USAGE



Dear respondents,

We are Diploma in Business Studies Students from Commerce Department, Politeknik

Sultan Salahuddin Abdul Aziz Shah. We are conducting survey to complete our Final Year

Project. The survey is about The Factors Influence Food Delivery Applications Usage Among

Students of Politeknik Sultan Salahuddin Abdul Aziz Shah During Movement Control Order

(MCO).

The purpose of this study is to study on Factors Influence Food Delivery Applications

Usage Among Students of Politeknik Sultan Salahuddin Abdul Aziz Shah During Movement

Control Order (MCO).

We can assure that all the answers provided by you will be strict confidentially and

used for our future research. Here, we would like to take this opportunity to thank you for your

precious time in giving us your feedback in this survey/questionnaire.

NAME MATRIC NO.

NURUL SYAZWANI BINTI ZAKARIA 08DPM18F1040

NUR SYAFIQA BINTI ROSLI 08DPM18F1057

BATRISYIA BINTI SOBIE 08DPM18F1070

ANNUR BINTI ABDUL RAZAK 08DPM18F1077

54

RESEARCH TOPIC:

The Factors Influence Food Delivery Applications Usage among Students of Politeknik

Sultan Salahuddin Abdul Aziz Shah during Movement Control Order (MCO)

Survey Questionnaire

Dear respondent, The purpose of this survey is to study The Factors Influence Food

Delivery Applications Usage among Students of Politeknik Sultan Salahuddin Abdul

Aziz Shah during Movement Control Order (MCO).

Thank you for your participation.

Instruction:

1) There are TWO (2) sections in this questionnaire. Please answer ALL questions in

ALL sections.

2) Completion of this form will take approximately 15 minutes.

3) The contents of this questionnaire will be kept strict confidential

55

Section A: Demographic Profile

Please indicate (✔) in the appropriate information about yourself. Each question should only

have ONE answer.

2. Gender

Male Female

2. Age

18 and below 19 – 22 23 and above

3. Marital status

Single Married

4. Income

Below RM 400 RM 401 – RM 800

RM 801 – RM 1,200 RM 1,201 and above

5. Course of study

Business Non-business

6. Do you own a smartphone

Yes No

7. Have you ever downloaded applications for your mobile device?

Yes No

8. Do you know about Food Delivery Applications?

Yes No

9. Which food delivery applications have you downloaded?

Food Panda Dah Makan

Grab Food Others:_________________

56

Section B: Independent and Dependent Variables

Please indicate how strongly you agree or disagree with the statement given on the following

Likert scale. Please circle the number which best describes your response.

(1) = strongly disagree; (2) = disagree; (3) = neutral; (4) = agree; (5) = strongly agree

Food Delivery Applications (Dependent Variable)

No. Question 1 2 3 4 5

1. I am familiar with food delivery applications. 1 2 3 4 5

2. I know about food delivery applications through

advertisement on social media. 1 2 3 4 5

3. I do realize about the existence of food delivery

applications until now. 1 2 3 4 5

4. I do have an experience of food delivery applications. 1 2 3 4 5

5. I have heard about food delivery applications. 1 2 3 4 5

Social Influence (1st Independent Variable)


1. People who are important to me think that I should use

food delivery applications for purchasing foods. 1 2 3 4 5

2. People who influence my behaviour think that I should

use food delivery applications for purchasing foods.

1 2 3 4 5

3. People whose opinions I value prefer that I use food

delivery applications for purchasing foods. 1 2 3 4 5

57

Facilitating Conditions (2nd Independent Variable)


1. I have the knowledge necessary to use food delivery

applications for purchasing foods. 1 2 3 4 5

2. I feel comfortable using food delivery applications for

purchasing foods.

1 2 3 4 5

Habit (4th Independent Variable)


1. Purchasing foods through food delivery applications is


1 2 3 4 5

2. I am addicted to using food delivery applications for the

purchase of foods.

1 2 3 4 5

3. I must use food delivery applications for purchasing

foods.

1 2 3 4 5

4. Using food delivery applications for purchasing foods

has become natural to me.

1 2 3 4 5

58

APPENDIX C: CRUCIAL INFORMATION

FDA 1 (I am familiar with food delivery applications)

Frequency Percent Valid Percent Cumulative

Percent

Valid

Disagree 9 2.5 2.5 2.5

Neutral 33 9.2 9.2 11.8

Agree 127 35.6 35.6 47.3

Strongly agree 188 52.7 52.7 100.0

Total 357 100.0 100.0

FDA 2 (I know about food delivery applications through advertisements on social

media)


Percent

Valid

Strongly disagree 1 .3 .3 .3

Disagree 8 2.2 2.2 2.5

Neutral 40 11.2 11.2 13.7

Agree 131 36.7 36.7 50.4

Strongly agree 177 49.6 49.6 100.0

Total 357 100.0 100.0

59

FDA 3 (I do realize about the existence of food delivery applications until now)


Percent

Valid

Disagree 6 1.7 1.7 1.7

Neutral 14 3.9 3.9 5.6

Agree 112 31.4 31.4 37.0

Strongly agree 225 63.0 63.0 100.0

Total 357 100.0 100.0

FDA 4 (I do have an experience of food delivery applications)


Percent

Valid


Disagree 5 1.4 1.4 2.2

Neutral 47 13.2 13.2 15.4

Agree 103 28.9 28.9 44.3

Strongly agree 199 55.7 55.7 100.0

Total 357 100.0 100.0

FDA 5 (I have heard about food delivery applications)


Percent

Valid

Disagree 2 .6 .6 .6

Neutral 6 1.7 1.7 2.2

Agree 111 31.1 31.1 33.3

Strongly agree 238 66.7 66.7 100.0

Total 357 100.0 100.0

60

SI 1 (People who are important to me think that I should use food delivery applications

for purchasing foods)


Percent

Valid


Disagree 15 4.2 4.2 4.8

Neutral 83 23.2 23.2 28.0

Agree 118 33.1 33.1 61.1

Strongly agree 139 38.9 38.9 100.0

Total 357 100.0 100.0

SI 2 (People who influence my behaviour think that I should use food delivery

applications for purchasing foods)


Percent

Valid

Strongly disagree 5 1.4 1.4 1.4

Disagree 31 8.7 8.7 10.1

Neutral 108 30.3 30.3 40.3

Agree 150 42.0 42.0 82.4

Strongly agree 63 17.6 17.6 100.0

Total 357 100.0 100.0

61

SI 3 (People whose opinions I value prefer that I use food delivery applications for

purchasing foods)


Percent

Valid


Disagree 21 5.9 5.9 7.3

Neutral 102 28.6 28.6 35.9

Agree 161 45.1 45.1 81.0

Strongly agree 68 19.0 19.0 100.0

Total 357 100.0 100.0

FC 1 (I have the knowledge necessary to use food delivery applications for purchasing

foods)


Percent

Valid


Disagree 12 3.4 3.4 4.5

Neutral 30 8.4 8.4 12.9

Agree 146 40.9 40.9 53.8

Strongly agree 165 46.2 46.2 100.0

Total 357 100.0 100.0

62

FC 2 (I feel comfortable using food delivery applications for purchasing foods)


Percent

Valid

Disagree 12 3.4 3.4 3.4

Neutral 20 5.6 5.6 9.0

Agree 122 34.2 34.2 43.1

Strongly agree 203 56.9 56.9 100.0

Total 357 100.0 100.0

HABIT 1 (Purchasing foods through food delivery applications is almost like a habit for

me)


Percent

Valid


Disagree 88 24.6 24.6 31.4

Neutral 100 28.0 28.0 59.4

Agree 91 25.5 25.5 84.9

Strongly agree 54 15.1 15.1 100.0

Total 357 100.0 100.0

63

HABIT 2 (I am addicted to using food delivery applications for the purchase of foods)


Percent

Valid


Disagree 63 17.6 17.6 24.6

Neutral 115 32.2 32.2 56.9

Agree 79 22.1 22.1 79.0

Strongly agree 75 21.0 21.0 100.0

Total 357 100.0 100.0

HABIT 3 (I must use food delivery applications for purchasing foods)


Percent

Valid


Disagree 38 10.6 10.6 13.4

Neutral 119 33.3 33.3 46.8

Agree 75 21.0 21.0 67.8

Strongly agree 115 32.2 32.2 100.0

Total 357 100.0 100.0

64

HABIT 4 (Using food delivery applications for purchasing foods has become natural to

me)


Percent

Valid


Disagree 48 13.4 13.4 14.6

Neutral 94 26.3 26.3 40.9

Agree 84 23.5 23.5 64.4

Strongly agree 127 35.6 35.6 100.0

Total 357 100.0 100.0

65

APPENDIX D: DESCRIPTIVE STATISTICS

Food Delivery Applications (Dependent Variable)

Descriptive Statistic

N Minimum Maximum Mean Std. Deviation

I am familiar with food delivery

applications. 357 2 5 4.38 .758

I know about food delivery

applications through

advertisement on social media.

357 1 5 4.33 .784

I do realize about the existence

of food delivery applications

until now.

357 2 5 4.56 .654

I do have an experience of food

delivery applications. 357 1 5 4.37 .827

I have heard about food

delivery applications. 357 2 5 4.64 .547

66

Social Influence (1st Independent Variable)



People who are important to me

think that I should use food


purchasing foods.

357 1 5 4.06 .916

People who influence my

behaviour think that I should

use food delivery applications


357 1 5 3.66 .915

People whose opinions I value

prefer that I use food delivery


foods.

357 1 5 3.75 .880

67

Facilitating Conditions (2nd Independent Variable)



I have the knowledge necessary

to use food delivery


foods.

357 1 5 4.28 .841

I feel comfortable using food


purchasing foods.

357 2 5 4.45 .750

68

Habit (3th Independent Variable)



Purchasing foods through food

delivery applications is almost

like a habit for me.

357 1 5 3.18 1.161

I am addicted to using food

delivery applications for the

purchase of foods.

357 1 5 3.32 1.190

I must use food delivery


foods.

357 1 5 3.69 1.114

Using food delivery


foods has become natural to

me.

357 1 5 3.79 1.103

69

APPENDIX E: RELIABILITY TEST

Food Delivery Applications

N Valid 357

Missing 0

Mean 4.46

Std. Deviation .560

Social Influence

N Valid 357

Missing 0

Mean 3.50

Std. Deviation .964


N Valid 357

Missing 0

Mean 4.36

Std. Deviation .745

Habit

N Valid 357

Missing 0

Mean 3.82

Std. Deviation .783

70

APPENDIX F: CORRELATION TEST

Correlations

TFDA TSI TFC THABIT

FOOD

DELIVERY

APPLICATION

Pearson Correlation 1 .441** .657** .417**

Sig. (2-tailed) .000 .000 .000

N

357 357 357 357

SOCIAL

INFLUENCE

Pearson Correlation .441** 1 .436** .366**

Sig. (2-tailed) .000 .000 .000

N 357 357 357 357

FACILITATING

CONDITION

Pearson Correlation .657** .436** 1 .359**

Sig. (2-tailed) .000 .000 .000

N 357 357 357 357

HABIT Pearson Correlation .417** .366** .359** 1

Sig. (2-tailed) .000 .000 .000

N 357 357 357 357

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

71

APPENDIX G: SWOT ANALYSIS

STRENGTHS

Well-known applications

Variety of products

High demand during pandemic

Covid-19

WEAKNESS

Many competitors

OPPORTUNITIES

Market development

THREATS

Instability economy

Fluctuating currencies

72

APPENDIX H: GANTT CHART

Activities Week

1

Week

2

Week

3

Week

4

Week

5

Week

6

Week

7

Week

8

Week

9

Week

10

Week

11

Week

12

Week

13

Week

14

Week

15

Form a group

Choose title

Determine supervisor ✔

Discuss about the issue

Discuss proposal introduction ✔

Checking Chapter 1 with supervisor ✔

Discuss about research objectives

Discuss about Chapter 2 ✔

Discuss about Chapter 1 until Chapter 3 ✔

Discuss about Topic 1 until Topic 3

Discuss about questionnaire ✔

Checked proposal Chapter 1 until

Chapter 3 ✔

Present the proposal to supervisor

Checked the proposal with supervisor ✔

Discuss about hypothesis

Do questionnaire ✔

Discuss and checked questionnaire ✔

Develop questionnaire ✔

Checked pilot test using SPSS

Proceed to analysed population

Reliable data

✔

Distributed actual data among Students of

Politeknik Sultan Salahuddin Abdul Aziz

Shah

✔

Analysis data ✔ ✔

Prepared report ✔

Final report ✔

Present Final Year Project (FYP) ✔

Documents

REPORT THE FACTORS INFLUENCE FOOD DELIVERY ...repository.psa.edu.my/bitstream/123456789/2527/1/THE...NURUL SYAZWANI BINTI ZAKARIA 08DPM18F1040 2. NUR SYAFIQA BINTI ROSLI 08DPM18F1057