Factors affecting gen zs online shopping behavior in hanoi in 2022

Untitled Banking Academy of Vietnam International school of Business Factors affecting Gen Z''''s online shopping behavior in Hanoi in 2022 Lecturer PhD Dinh Thi Thanh Binh Class CityU9A Group 7 Members[.]

Banking Academy of Vietnam International school of Business

Factors affecting Gen-Z's online shopping behavior

in Hanoi in 2022

Lecturer: PhD Dinh Thi Thanh Binh

Class: CityU9A

Group 7

Members of team:

Phan Anh Dũng CA9-016 (25%)

Nguyễn Kiều Linh CA9-040 (25%)

Dương Quỳnh Phương CA9-059 (25%)

Vũ Hoàng Long CA9-045 (25%)

Hà Nội, 8 tháng 12 năm 2022

Contents

Introduction 1

Chapter 1: Theoretical and practical basis of research subjects and a number of main factors 2

1.1 Definition 2

1.2 Literature review on the factors effecting the Online shopping frequency of GenZ in Hanoi area 2

Chapter 2: Research methodology and econometric model 3

2.1 Method Research 3

2.1.1 Model building method 3

2.1.2 Methods of data collection and processing 4

2.2 Building econometric models 5

2.2.1 A random sample regression model 5

2.3 Description of the data 6

2.3.1 Data source 6

2.3.2 Describe the statistics 6

Chapter 3: Quantitative Analysis 8

3.1 Regression model 8

3.2 Analyze the results after run regression mode 8

3.3 Meaning of Partial Regression Coefficients 9

3.4 Check the suitability of the model 9

3.5 Check the model's defects 10

3.5.1: Multicollinearity 10

3.5.2 Variable error variance 12

Chapter 4 Hypothesis test 13

4.1 Wage test 13

4.2 Onl test 13

4.4 Gen test 14

4.5 Lvp test 14

4.6 Std test 15

Conclusion 16

References 17

Introduction

In recent years, online shopping is becoming more and more popular with many generations of consumers in the digital transformation era, especially during the

Covid-19 era, creating new shopping habits and cultures Regarding the change in consumer behavior, there is a report that 58% of Vietnamese consumers think that they will continue to shop for groceries on e-commerce platforms because of convenience Generation Z are the ones who create new trends, make an impact in the consumer segment, are the object of fast access to online shopping because of frequent use of online tools and easy to update online shopping trends Besides, they also have the ability to influence family decisions in general shopping activities (Nielsen, 2021) Therefore, Gen Z is a very important customer that needs to be studied

Hanoi, the Capital of Vietnam, contributes the second largest share (11%) to total retail sales in Vietnam and online shopping has become extremely popular among the residents of this city Therefore, the authors conducted a survey and research on online shopping behavior and the relationship between demographic factors and online shopping frequency of Gen Z subjects in Hanoi in the context of context of the

Covid-19 pandemic, through which to propose some solutions to help businesses and retailers that provide online sales services make more appropriate adjustments to meet the expectations of gen Z customers after making an online purchase

This essay use table data analysis methods to study and analyze some determinants of the GenZ’s shopping behavior in Hanoi in the year 2022 The research object is the degree of influence of the six main influencing factors, which are: wage, online time, age, gender, living place, level of study By applying the knowledge from econometrics with socio-economic knowledge to analyze and find relationships between variables, the essay of the research team will answer the questions: How do the main factors affecting frequency of online purchases of Gen Z? What is the level of impact? What should sellers do to attract more of these customers? During the research process, usage data was collected from google forms and used econometric analysis tools, STATA software to analyze and research based on data

The essay of our research team contains 4 chapters:

Chapter 1: Rationale and research hypothesis, and econometric model

Chapter 2: Research methodology and econometric model

Chapter 3: Estimation, model testing, and statistical inference

Chapter 4: Solutions and recommendations

Due to many limitations of expertise and circumstances, the essay cannot avoid errors and omissions The research team is looking forward to receiving the comments of the subject lecturers to be able to complete the essay better

Our team sincerely thank you!

Chapter 1: Theoretical and practical basis of research subjects and a number of

main factors 1.1 Definition

Online shopping frequency is Purchase Frequency is the number of times that a

customer makes a purchase in a given period of time In this case, the frequency of a consumer's online shopping is measured by the number of times they made an online purchase in the last six months Purchase frequency represents how often GenZ performs online shopping We use 4 levels from 1 to 4 to represent this variable, the higher the level, the more frequent purchases and vice versa

In recent years, online shopping is becoming more and more popular with many generations of consumers in the digital transformation era, especially during the

Covid-19 era, creating new shopping habits and cultures Regarding the change in consumer behavior, there is a report that 58% of Vietnamese consumers think that they will continue to shop for groceries on e-commerce platforms because of convenience Generation Z are the ones who create new trends, make an impact in the consumer segment, are the object of fast access to online shopping because of frequent use of online tools and easy to update online shopping trends Besides, they also have the ability to influence family decisions in general shopping activities (Nielsen, 2021) Therefore, Gen Z is a very important customer that needs to be studied

Hanoi, the Capital of Vietnam, contributes the second largest proportion (11%) to total retail sales in Vietnam and online shopping has become extremely popular among the residents of this city Therefore, the authors conducted a survey and research on online shopping behavior and the relationship between demographic factors and online shopping frequency of Gen Z subjects in Hanoi to propose proposed a number of solutions to help businesses and retailers that provide online selling services make more appropriate adjustments to meet the expectations of Gen Z after buying online

1.2 Literature review on the factors effecting the Online shopping frequency of GenZ in Hanoi area

In general, both domestically and internationally there have been research papers on the impact of Covid-19 on the shopping behavior of gen Z and the influence of some demographic factors on people's online shopping behavior Specifically, can include: Consumers of all generations during the Covid-19 crisis tend to buy goods and services online (Jílková, P.; Králová, P., 2021) Sethuraman (2020) points out that the Covid-19 epidemic has increased the demand for food, grocery and healthcare delivery at home Gen Z in Croatia who have been self-isolating at home because of the Covid-19 pandemic say they shop online more than they did before the pandemic (Leko Šimić & Pap, 2021)

Regarding the impact of some demographic factors, according to Gurmu & Etana (2014), age is an important demographic aspect affecting online purchasing behavior,

as purchasing decisions will change by age Young people tend to spend more on

lifestyle, entertainment, fashion, while older people spend most on health-related expenses Average income also plays an important role influencing online purchasing behavior (Ryscavage, 2015) Low-income people approach online shopping with caution due to a lower tolerance for financial loss than high-income people (Gunes, 2018)

Besides, in the country, there is also a research paper by the authors Nguyen Minh Hieu, Jimmy Armoogum and Nguyen Thi Binh (2021) indicating that women tend to shop online more often This may be because women in Vietnam are often responsible for household chores and taking care of other family members So, when they have difficulty with going to shop in person, they will be the pioneers to implement online shopping as an alternative

However, in reality in Vietnam today, there are still very few studies that go into analysis of the relationship between demographic factors and the online shopping frequency of gen Z Therefore, the purpose of this study is online shopping behavior and the relationship between demographic factors and online shopping frequency of Gen Z subjects in Hanoi in the context of the Covid-19 pandemic, in order to help businesses can have more ways to attract these customers on online shopping channels Based on a study we just learned, we decided to choose 7 variables for the

model, including:

Dependent variable: Frq Online purchase frequency (Unit: Level(s))

Independent variables:

- Wage WGL (Unit: Levels)

- Online times ONL (Unit: Levels)

- Ages AGL (Unit: Levels)

- Gender GEN (Unit: 0 1)

- Living place LVP (Unit: 0 1)

- Study levels STD (Unit: Levels)

Chapter 2: Research methodology and econometric model

2.1 Method Research

2.1.1 Model building method

Regression analysis method: Find the dependencies of a variable, called the dependent variable on one or more other variables, called independent variables for the purpose of estimating or predicting the expected value of the foreseeable values of the independent variable, specifically in this study, analyzing the relationship between the

independent variable (Wage, Online times, Ages, Gender, Living place, Study levels) and dependent variable (Online purchase frequency)

2.1.2 Methods of data collection and processing

- Methods of data collection

For secondary data:

Our team collects data from other scientific research papers, articles in newspapers or scientific journals that specialize in the subject

For primary data:

To reduce survey costs and time, our study uses a convenient sampling method Targeted are people of Gen Z (aged 10-25), who are living in Hanoi and have been shopping online

The survey process was conducted from 01/12/2022 to 05/12/2022 After screening and removing invalid 26 answers, it is finally possible that the number of survey votes taken into the analysis will be 114 The data is distributed fairly evenly over gender, as well

as two geographical regions in the peak and non-peak districts of Hanoi

The survey respondents were Z genes, so the number of responses that studying in college/university degree was quite large (78.3%), 12.2% had a bachelor's degree and only 9.6% were in secondary school Respondents had less than 5 million VND per month in personal income, accounting for 54.8%, but more than 19% earned over 10 million VND per month Regarding internet usage, the majority of people who spend less than 5 hours a day on the internet, 40% spend two to five hours a day, and the

number of people who spend less than 2 hours a day on the internet is only 18.3%

- Data processing method

By estimating the coefficients of the normal minimum average model OLS, the data

is selected and checked the statistical significance of the regression coefficients and the suitability of the model based on observations, also as compared to previous and similar studies to find the best results to use for analysis During the homework, the group used the knowledge of econometrics and macroeconomics, quantitative methods with the main support of STATA, Microsoft Excel, and Microsoft Word software to synthesize and complete this essay

Additionally, for variables measured using quantitative intervals such as Frq, Wage, Online time, Ages and Std, our team converts the data into Levels 1 to 3 and 4 by the

command: encode (var),gen(new var) The higher the level, the higher the level of

performance, value, volume, frequency and vice versa Especially in the Lvp (place of residence), my team classified the districts in Hanoi from the original data into 2 regions: key areas (Hoan Kiem District, Ba Dinh District, Dong Da District, Hai Ba Trung District) and non-key areas (remaining counties)

2.2 Building econometric models

After studying and referencing studies that have been done before, our team decided

to use multiple regression analysis to find out the dependence of FRQ and dependent variable for 6 independent Wage, Online times, Ages, Gender, Living place, Study levels for the Year 2022

The model consists of 7 variables:

Dependent variable: FRQ Online purchase frequency (Unit: Level(s))

Independent variables:

- Wage WGL (Unit: Levels)

- Online times ONL (Unit: Levels)

- Ages AGL (Unit: Levels)

- Gender GEN (Unit: 0 1)

- Living place LVP (Unit: 0 1)

- Study levels STD (Unit: Levels)

2.2.1 A random sample regression model

I = 𝛽1+ 𝛽2WGL + 𝛽3 ONL+ 𝛽4AGL + 𝛽5GEN+ 𝛽6LVP + 𝛽7STD + ui

𝛽1: estimate of intercept

𝛽2: the estimated slope of the variable WGL

𝛽3: the estimated slope of the variable ONL

𝛽4: the estimated slope of the variable AGL

𝛽5: the estimated slope of the variable GEN

𝛽6: the estimated slope of the variable LVP

𝛽7: the estimated slope of the variable STD

ui: remainder, estimate of random error

2.3 Description of the data

2.3.1 Data source

- Scientific research papers, articles in newspapers or scientific journals that specialize

in the subject

- Data found from the Google Form

- Sample space: The survey was conducted in Hanoi area, with 2 focus areas and non-key areas Therefore, it can be said that this sample space is large enough, objective and reliable enough to build up a regression model

2.3.2 Describe the statistics

In order to help the reader have the most overview as well as give some initial assessment, the group will describe the data before proceeding to analyze the data Through this description, the team is able to predict some possible errors when running the model due to lack of data

The figures include: Wage (WGL), Online times (ONL), Ages (AGL), Gender (GEN), Living place (LVP), Study levels (STD) for the Year 2022

Table 2.1 Statistical description of the variables

sum frq wgl onl agl gen lvp std

Variable | Obs Mean Std Dev Min Max

-+ -

frq | 114 2.429825 1.080555 1 4

wgl | 114 1.929825 .6746916 1 3

onl | 114 2.210526 .7344095 1 3

agl | 114 1.894737 .4678783 1 3

gen | 114 .4210526 .4959078 0 1

lvp | 114 .2631579 .4422915 0 1

std | 114 2.026316 .4696172 1 3

-+ -

With the purchase frequency variable, up to 12 people with a high frequency of online

purchases clicked more than 10 times a month (level 4) compared to the lowest level of

1 to 2 times a month (level 1) of 35 other people On average, these young people shop online at 2.5 times, that is, between level 2 (3-5 times/month) and level 3 (6-10 times/month)

Next, 22 people have the highest monthly income of over 10 million VND a month

(level 3), while the majority have income from level 1 (under 5 million VND), about 63 people The average income of those who fill out the form is around 2 (5-10 million VND/month)

Considering the maximum online time, level 3 (over 5 hours/day), up to 41.7% of

applicants belong to this region, almost equal to level 2 (40%), the rest level 1 (under 2 hours) /day) only accounts for 18.3% On average, most GenZ spend time online at level 2 (2-5 hours/day)

When it comes to age level, with the largest age group 3 (over 25 years old) there are

only 7 people, while the lowest level (level 1) is only 19 people, so the rest (level 2 –

19 to 25 years old) ) is the most numerous The average age of applicants is close to level 2

Regarding gender with Mean 0.42 < 0.5, it can be said that the number of respondents

is female (0) with 67 votes more than male (1) with 48 votes

The variable lvp is divided into 2 areas, the central area of Hanoi (1) has only 22 people

living while the remaining areas are up to 92 votes The mean of the variable 0.26 also showed that difference

Finally, the STD variable, generally with an average level of about 2 (currently studying

at University / College), it can be said that the majority of survey participants are GenZ subjects that the group is targeting, besides The highest level is level 3 (graduated) only 12.2% and the lowest level is level 1 (middle school/high school) accounting for only 9.6%

Chapter 3: Quantitative Analysis 3.1 Regression model

Table 3.1 Regression Model

reg frq wgl onl agl gen lvp std

Source | SS df MS Number of obs = 114 -+ - F(6, 107) = 2.52 Model | 16.3327313 6 2.72212188 Prob > F = 0.0255 Residual | 115.605865 107 1.08042865 R-squared = 0.1238 -+ - Adj R-squared = 0.0747 Total | 131.938596 113 1.1675982 Root MSE = 1.0394

- frq | Coef Std Err t P>|t| [95% Conf Interval] -+ - wgl | -.2105482 .1487165 -1.42 0.160 -.5053613 084265 onl | .2585366 .1391761 1.86 0.066 -.0173637 534437 agl | .052408 .2788959 0.19 0.851 -.5004706 .6052865 gen | -.4680162 .1998624 -2.34 0.021 -.8642201 -.0718124 lvp | .1972811 .2239213 0.88 0.380 -.2466167 .6411789 std | .206545 27803 0.74 0.459 -.344617 .7577071 _cons | 1.891962 .6470672 2.92 0.004 609227 3.174697 -

3.2 Analyze the results after run regression mode

From the table above we have the sample regression equation SRF:

+ 0.1972811*lvp – 0.206545*std + u ^

The model shows that: Wage, Online times, Ages, Gender, Living place, Study levels have effects on Online shopping frequency

It means that the independent variable (Wage, Online times, Ages, Gender, Living place, Study levels) in the model can explain 12.38% of the variation of Online shopping frequency