TOPIC FACTORS INFLUENCING THE FREQUENCY OF USING ONLINE FOOD DELIVERY OF UNIVERSITY STUDENTS IN HO CHI MINH CITY

LÊ HẰNG MỸ HẠNH TOPIC FACTORS INFLUENCING THE FREQUENCY OF USING ONLINE FOOD DELIVERY OF UNIVERSITY STUDENTS IN HO CHI MINH CITY Group: Community Class: K58CLC5 Class code: 203 Ho Chi Mi

FOREIGN TRADE UNIVERSITY

IN HO CHI MINH CITY -★★★

-GROUP REPORT

SUBJECT: ECONOMETRICS

INSTRUTOR: MRS LÊ HẰNG MỸ HẠNH

TOPIC FACTORS INFLUENCING THE FREQUENCY OF USING ONLINE FOOD DELIVERY OF UNIVERSITY STUDENTS IN HO CHI MINH CITY

Group: Community Class: K58CLC5 Class code: 203

Ho Chi Minh City – 06/2021

Table of contents

TABLE OF CONTENTS

2. OTHER SOLUTIONS TO “TOO-BIG-TO-FAIL” PROBLEM 9

Danh sách thành viên – Danh mục hình ảnh

LIST OF FIGURES

Figure 3 The first too-big-to-tail problem arose with Continential Illinois 3 Figure 4 Dodd-Frank Wall Street Reform and Consumer Protection Act 3

Figure 6 Less fear of the big impacts of the failure of a group of banks 8

LIST OF TABLES

Table 1 5 out of 100 biggest banks ranked both by reported total assets and total assets when

derivatives are on a gross, not net (U.S GAAP) in some countries in 2012 4

GROUP MEMBER LIST

Chapter 1: Introduction

CHAPTER 1: INTRODUCTION

Living in an era where technology is advancing at an unprecedented rate, consumers are becoming smarter and more demanding than ever before With the existence of many new products and services, consumers now have plenty of options in terms of price, quality and especially, convenience A busy lifestyle is a signature in this modern time, people barely have time for themselves when most of their time is spent on work Briefly speaking, they want to save as much time as possible That is the main reason why 75% of the total Vietnamese population have used Food Delivery Service because they find cooking meals, or even eating out, very time-consuming What is remarkable is that 25% of them are new users who have started to use food delivery services for the first time due to Covid-19, which means safety from the pandemic is the second most significant reason explaining the rise of Food Delivery Service Among some ordering methods, Online Food Delivery Service Application is the most popular one when greater than 90% use this to order food and drinks

The Vietnam’s Online Food Delivery Service market is driven by increasing internet and smartphone penetration, along with an increase in the number of restaurants and other food chains Aided by the technical advancements in the Vietnam’s Online Food Delivery Service market, it is expected to witness a healthy growth in the forecast period of 2021-2026, growing

at a CAGR of 24% At present, this market is facing fierce competition with the existence of major brands such as Grabfood, Now, Baemin, Gofood, and Loship However, recently, the entry of domestic enterprises such as VinID and Tiki is considered to re-divide the market share

of this potential "piece of cake" Although the Online Food Delivery Service Application market

is booming with the participation of many players sharing the pie, having an available strong customer base will retain the firm’s position and make it harder for other brands to enter the market Therefore, besides attempts to raise brand awareness and attract new customers, brands must invest in advancing the company and the application itself to keep its current customers and turn them into loyal ones

The objective of this research is to study the factors that influence the frequency of ordering food and drinks from Online Food Delivery Service Applications To be more practical, the research helps Online Food Delivery Service firms to have a better insight of customers by providing information about which factors may limit the number of times a customer demands for Online Food Delivery Service Applications Thus, firms can create an effective strategy not only to meet customers’ needs but even exceed their expectations

Chapter 2:Literature review

CHAPTER 2: LITERATURE REVIEW

1 OVERVIEW OF FOREIGN RESEARCH

Today there are more than 10,000 studies, essays, large and small articles related to consumer behavior, purchasing behavior, and frequency of purchase in the world Among them must be the quality studies of Arian Oosthoek (2013); See Siew Sin, Khalil Md Nor, and Ameen M Al-Agaga (2012); Yogi Tri Prasetyo and his partners (2021); Haiyang Liu (2019) Here, the authors would like to present a summary of the results of the above works as a premise for the next steps of our research

In the research “What is the impact of Facebook tie strength and behavior on purchase intention?” by Arian Oosthoek, the author used systematic empirical investigation and survey to collect data, then applying multiple regression model and correlation coefficient

to analyze the data The results of the study reach four conclusions as follows

● Hypothesis 1: Strong ties on Facebook affect online purchase intention more than weak ties on Facebook.

● Hypothesis 2: Social ties on Social Media affect the purchase intention more for alow involvement luxury good.

● Hypothesis 3: The higher the Facebook activity, the higher the purchase

intention and attitude towards the product with strong ties.

● Hypothesis 4: People with higher income have a more positive attitude and intention toward the purchase of high involvement products.

In the study “Factors Affecting Customer Satisfaction and Loyalty in Online Food Delivery Service during the COVID-19 Pandemic: Its Relation with Open Innovation” of Yogi Tri Prasetyo and partners, the authors applied methods of the questionnaire, model fit, and structural equation modeling (SEM Model) Initially, there were 11 hypotheses stated on the causal relationships between variables but after the first time running the SEM Model it pointed out that several hypotheses were not important The final SEM model contained 4 exogenous variables, the two hedonic motivations and information quality affecting

“INTENTION TO USE” and the two prices and promotion affecting “ACTUAL USE”

Haiyang Liu with his research “ Factors positively influencing customer satisfaction of online food delivery services of customers in Bangkok and its vicinity” is based on the instrument of Cronbach’s Alpha Coefficient, Multiple Regression Analysis, and Pearson’s Correlation

Chapter 2:Literature review

Coefficient to study customer satisfaction There were two accepted hypotheses, the most

predictive independent variables were 38 hedonic motivations (β = 0.767), new experience

(β =0.163) Hedonic motivations and new experience could positively influence customer

satisfaction of OFD services of customers in Bangkok and its vicinity at 52%, the rest 48%

were affected by any other variables, these variables were not used in this paper The

result of VIF value was not more than 4 and the tolerance value exceeded 0.2, indicating

that there was not Multicollinearity in the independent variables Thus, the standard error

equaled ±0.492, the calculation as:

(customer satisfaction) (hedonic motivations) (new experience) This study can offer benefits for restaurants and other food industries in respect of

44 potential new markets of online purchase, online strategy improvement, or

investment decision for online food business in the future regarding factors

predicting the customer satisfaction towards online food delivery services.

In general, foreign research above quite specifically analyzes the factors affecting

customers’ online purchase decisions and offers specific solutions for their countries Here,

the authors would like to use the above quality studies for reference purposes and as a

base to build a model for research in Vietnam, specifically Ho Chi Minh City

2 OVERVIEW OF DOMESTIC RESEARCH

In Vietnam, there have been many typical studies such as “Research on online

food ordering behavior of customers aged 18 - 30 in Ho Chi Minh City”, “Research

on factors affecting online shopping decisions of consumers of university students

in Ho Chi Minh City” or “Factors affecting the behavior of using public transport that

has technology applications – A case study with Grab Bike service”.

In the study “Research on factors affecting online shopping decisions of consumers of university

students in Ho Chi Minh City”, the results show that the scales are reliable through the

Cronbach Alpha test However, EFA analysis explained that the scale of

CHAMSOCKHACHHANG components was excluded The remaining 6 factors perceived

usefulness, perceived convenience in payment, perceived ease of use, trust, influence from

external factors and price expectations continued to go into the ANOVA analysis The results

Chapter 2:Literature review

show that the factor “Influence from external factors” was not eligible to participate

in this model, so it should be removed The remaining 5 factors are proportional to the decision on the purchase price of consumer products of university students in

Ho Chi Minh City It proves that the proposed theoretical model is consistent with current reality as well as the hypotheses in the theoretical model are accepted.

Dr Nguyen Binh Minh and his partners (2017) with the research “Factors affecting the behavior

of using public transport that have technology applications – A case study with Grab Bike service” applied Cronbach’s alpha and the multiple regression model to analyze the data They concluded that the analysis factors all have a positive impact on the usage behavior of customers The results provide suggestions for managers and marketers to pay attention to quality factors, safety, and ease of use In addition, factors such as "subjective standards' ';

"perceived usefulness" also need attention As for the "usefulness" factor, especially taking advantage of technology and saving time to create a difference and advantage in competition

In general, researchers in Vietnam mainly analyze online buying behavior, but they are somewhat incomplete Researches in Vietnam often pay little attention to providing solutions for enterprises or give them an unsatisfactory, unrealistic, or unfounded way Therefore, in our research, we will overcome the mistakes and shortcomings of previous studies to research and provide effective and appropriate solutions to develop the field of online food ordering in Vietnam.

Chapter 3: Methodology and data

CHAPTER 3: METHODOLOGY AND DATA

Chapter 4: Result

CHAPTER 4: RESULTS

Based on the respective internal consistency explained by the value of Cronbach’s Alpha

on the Appendix 1 on Page a, after conducting the scale reliability analysis by Cronbach’s Alpha on Stata, we receive the result of Cronbach’s Alpha as the tables below indicates:

● With the scale of the variable PROMO, there are 3 smaller encoded variables including Promo1, Promo2 and Promo3.

Table 1 Cronbach’s Alpha of the Model – Group 1

The overall Cronbach’s Alpha of Group 1 is 0.8381 (0 8≤ α < 0 9) which means that the internal consistency in this variable group is good Moreover, the item-rest correlation of the variables Promo1, Promo2 and Promo3 are 0.7083, 0.7489 and 0.6945 respectively (> 0 4)

⇨ It is concluded that Promo1, Promo2 and Promo3 are well qualified for the PROMO variable and there would be no variable necessarily excluded from the variable group

● With the scale of the variable BARRIER, there are 3 smaller encoded variables including BAR1, BAR2 and BAR3.

Table 2 Cronbach’s Alpha of the Model – Group 2

Chapter 4: Result

The overall Cronbach’s Alpha of Group 2 is 0.8438 (0 8≤ α < 0 9) which means that the internal consistency in this variable group is good Moreover, the item-rest correlation of the variables BAR1, BAR2 and BAR3 are 0.7250, 0.6860 and 0.7208 respectively (> 0 4)

⇨ It is concluded that BAR1, BAR2 and BAR3 are well qualified for the BARRIER variable and there would be no variable necessarily excluded from the variable group

● With the scale of the variable CS, there are 4 smaller encoded variables

including CS1, CS2, CS3 and CS4.

Table 3 Cronbach’s Alpha of the Model – Group 3

The overall Cronbach’s Alpha of Group 3 is 0.6937 (0 8≤ α < 0 9) which means that the internal consistency in this variable group is good Moreover, the item-rest correlation of the variables CS1, CS2, CS3 and CS4 are 0.5420, 0.0937, 0.5660 and 0.7306 respectively ( > 0.4)

⇨ It is concluded that CS1, CS3 and CS4 are well qualified for the CS variable and there would be variable CS2 necessarily excluded from the variable group.

2 EXPLORATORY FACTOR ANALYSIS

After conducting the exploratory factor analysis (EFA) on Stata with the minimum value of eigenvalue to be retained is 1 (which means that we will exclude the factor with the value of eigenvalue smaller than 1), we receive the result of factor analysis as the figure in the Appendix 2 on page a indicates:

Result: Exclude the factor with the eigenvalue smaller than 1 and retain the Factor1, Factor2 and Factor3, which can cumulatively altogether explain 74.66 percent of the deviation of the data.

Chapter 4: Result

● Rotation: orthogonal varimax displaying loading as blank when |loading| < 0.5

Result: There will be 3 main

variable groups including PROMO (Promo1, Promo2 and

Promo3), BARRIER (BAR1, BAR2 and BAR 3) and CS (CS1,

CS3 and CS4).

● Kaiser-Meyer-Olkin (KMO) Test

Running on Stata:

Result: KMO = 0.6277 (> 0 5)

⇨ The sampling adequacy for each variable in the model and for the complete model is moderate.

Between the dependent variable and independent variables, the correlation analysis using Pearson’s Correlation Coefficient of Payment, Income, Promo, Barrier and CS that affects the frequency of using online food delivery.

*Correlation is significant at the 0.1 level

From the analysis, it can be clearly seen that 4 independent variables Payment ( = 0 2123), Income ( = 0 3452), PROMO ( = 0 1405) and BARRIER ( =− 0 1826) will have an effect on the frequency of using online food delivery at the significant level 0.1 Meanwhile, the

Chapter 4: Result

independent variable CS ( =− 0 0139 ) will have no effect due to its insignificance

at the 0.1 level.

In statistics, the definition of Multicollinearity was, among all the independent variables, a

circumstance of a very positive relationship (StatisticSolutions, 2017) Higher multicollinearity proved the higher degree of correlation among independent variables which might cause deviation away from the true value Equally, multicollinearity should not appear as it could lead to incorrect interpreting of MRA results

After having a regression model, we use the variance inflation factor (VIF) to test multicollinearity The value for VIF starts at 1 and has no upper limit A general rule

of thumb for interpreting VIFs is as follows:

● A value of 1 indicates there is no correlation between a given explanatory

variable and any other explanatory variables in the model.

● A value between 1 and 5 indicates moderate correlation between a given explanatory variable and other explanatory variables in the model, but this is often not severe enough to require attention.

● A value greater than 5 indicates potentially severe correlation between a given explanatory variable and other explanatory variables in the model In this case, the coefficient estimates and p-values in the regression output are likely unreliable

From the appendix, we can see that the VIF value of each independent variable value between 1 and 5 meaning Multicollinearity does not exist in the independent variables