Factors affecting online shopping behavior of banking university students during the covid 19 pandemic

Qualitative research: to explore the factors affecting online shopping behavior of students during Covid time and adjust the scale of the factors in the proposed research model.. Domesti

BANKING UNIVERSITY OF HO CHI MINH CITY

NGUYEN DO NGOC TRAN

CODE: 52340101

SUPERVISOR PhD NGUYEN VAN THICH

HO CHI MINH CITY, 03 – 2021

BANKING UNIVERSITY OF HO CHI MINH CITY

NGUYEN DO NGOC TRAN

CODE: 52340101

SUPERVISOR PhD NGUYEN VAN THICH

HO CHI MINH CITY, 03 – 2021

The study discusses the factors affecting the online shopping behavior of banking university students during Covid 19 based on Ajzen and Fishbein's Theory of Reasoned Action (1980), Theory of Planned Behavior Theory of Planned Behavior-TPB) by Ajzen (1991) along with domestic and foreign referenced research articles on online shopping behavior such as: Ha Ngoc Thang (2016), Nguyen Le Phuong Thanh (2013), Javadi et al (2012), Neger and Uddin (2020), Alhaimer (2021) The questionnaire was posted to student groups of Banking University of Ho Chi Minh City The responses from students obtained through the questionnaire will be recorded through the researcher's email address After 1 month of collection, 160 valid responses were included in the analysis Data is analyzed according to the process from factor analysis to reliability test and regression analysis The results show that, subjective norm has the most important significance for online shopping behavior (with the largest coefficient), followed by attitude and perceived behavioral control, respectively

Thesis is study my own research results are honest, while no content has been previously published or content by others made except citations citation fully in the thesis

To complete this article, first of all, I would like to express my deepest gratitude to PhD Nguyen Van Thich - who wholeheartedly guided and helped me to complete this research Because of my limited knowledge, in the process of researching, I inevitably make mistakes, and I would like to receive suggestions from teachers

CHAPTER 1: GENERAL OVERVIEW 10

1.1 Background 10

1.2 The urgency of the topic 11

1.3 Research objectives 12

1.4 Research question 12

1.5 Research object and Research scope 12

1.6 Research Methods 13

1.7 Research content 14

1.8 Research contribution 14

1.9 Structure of research 15

CHAPTER 2: LITERATURE REVIEW 16

2.1 Basic Concepts 16

2.1.1 Online shopping concept 16

2.1.2 Concept of consumer behavior 16

2.1.3 Consumer decision-making process 17

2.2 General theories and research models of consumer behavior 19

2.2.1 Theory of Reasoned Action – TRA 19

2.2.2 Theory of Planned Behavior – TPB 20

2.3 Factors affecting online shopping behavior: 21

2.3.1 Attitude 21

2.3.2 Price 22

2.3.3 Subjective norms 22

2.3.5 Perceived risk 23

2.4 Overview of research 24

2.4.1 Domestic research 24

2.4.2 Foreign research 27

2.4.3 Proposed research model 30

CHAPTER 3: METHODOLOGY 32

3.1 Research design 32

3.1.1 Method of building a scale 32

3.1.2 Research scale 33

3.2 Choose a sample 39

3.2.1 Overall 39

3.2.2 Method of sampling 39

3.2.3 Sample size 40

3.2.4 Information gathering 40

3.2.5 Information gathering process 40

3.3 Statistical data analysis technique 41

3.3.1 Testing the reliability of a scale 41

3.3.2 Testing the reliability of the model 41

3.3.3 Correlation coefficient and regression analysis 42

3.4 Conclusion of chapter 3 42

CHAPTER 4: FINDING 44

4.1 Data analysis 44

4.1.1 Unsuitable answer sheets 44

4.2 Sample discription 45

4.3 Reliability analysis and appropriate scale 54

4.3.1 Testing of scale reliability by Cronbach's alpha coefficient 55

4.3.2 Exploratory factor analysis EFA 60

4.3.3 Testing of models and hypotheses 68

4.4 Summary of research results 72

CHAPTER 5: CONCLUSION AND RECOMMENDATION 74

5.1 Conclusion 74

5.2 Recommendations and suggestions 75

5.3 Research limit 76

REFERENCE 78

APPENDIX 1 82

APPENDIX 2 89

Abbreviation Original

Table 3 1 Summary of scale 37

Table 4 1: Statistics for gender 45

Table 4 2: Statistics for school year 45

Table 4 3: Statistics for major 46

Table 4 4: Statistics for income 47

Table 4 5: Statistics for How long have you been using Internet 48

Table 4 6: Statistics for How many hours in a day do you use the Internet 48

Table 4 7: Statistics for shopping sites do you usually buy during Covid? 49

Table 4 8: Statistics for products do you usually buy when shopping online 49

Table 4 9: Descriptive Statistics for Attitude 50

Table 4 10: Descriptive Statistics for Price 51

Table 4 11: Descriptive Statistics for Subjective norms 51

Table 4 12: Descriptive Statistics for Perceived behavioral control 52

Table 4 13: Descriptive Statistics for Perceived risk 53

Table 4 14: Descriptive Statistics for Online shopping behavior 54

Table 4 15: Reliability Statistics for Attitude 55

Table 4 16: Reliability Statistics for Price 55

Table 4 17: Reliability Statistics for Subjective norms 56

Table 4 18: Reliability Statistics for Perceived behavioral control first time 57

Table 4 19: Reliability Statistics for Perceived behavioral control second time 58

Table 4 20: Reliability Statistics for Perceived risk 58

Table 4 21: Reliability Statistics for Online shopping behavior 59

Table 4 22: KMO coefficient and 1st Bartlett's test 60

Table 4 23: Eigenvalues and % explaining factors first time 60

Table 4 24: Convergence coefficient of factors forming first time 61

Table 4 25: Discriminant value between observed variables first time 62

Table 4 26: KMO coefficient and 2nd Bartlett's test 63

Table 4 27: Eigenvalues and % explaining factors second time 63

Table 4 29: Discriminant value between observed variables second time 65

Table 4 30: KMO coefficient and Bartlett's test 66

Table 4 31: Eigenvalues coefficients and % explaining factors 66

Table 4 32: Convergence coefficient of forming factors 67

Table 4 33: Correlation between independent variable and dependent variable 68

Table 4 34: Model summary table 69

Table 4 35: ANOVA test table 69

Table 4 36: Hypothesis testing 70

Table 4 37: Standardized Coefficients 72

Model 1: Theory of Reasoned Action - TRA 20

Model 2: Theory of Planned Behavior – TP 21

Model 3: Research model in research of Thang (2016) 25

Model 4: Research model in research of Chau & Dao (2012) 26

Model 5: Research model in research of Javadi et al (2012) 28

Model 6: Research model in research of Neger and Uddin (2020) 29

Model 7: Research model 31

Model 8: Modified research model 69

CHAPTER 1: GENERAL OVERVIEW

1.1 Background

Nowadays, online shopping become more popular because of the convenience and speed

it offers Just one click to get what you need without going to the store Especially since the occurrence of Covid-19, it has changed the consumer trend and is very reasonable reason for the booming online shopping environment Winning will belong to the business that changes quickly and seizes the fastest opportunity Over the past few decades, the Internet has evolved into a vast global marketplace for the exchange of goods and services In many developed countries, the Internet has been used as an important means, providing a wide range of products with 24-hour availability and wide coverage According to Chen (2009), research on consumer online shopping behavior is one of the most important research programs in the past decade Online shopping (also known as online shopping and Internet buying / buying) refers to the process of purchasing a product or service through the Internet Online shopping has distinct advantages such as: Consumers can easily access product information from many different sources: websites, social networks (facebook, instagram, ) In particular, the websites providing product price comparison services from other websites have provided very good support for consumers in making online purchases The online form provides

a wide variety of products and services, especially clothing, electronics, toys, and cosmetics Most e-commerce exchanges allow customers to review a product after purchasing it Therefore, consumers can learn about products carefully before deciding

to buy Especially saving time for consumers, especially students while studying at school However, the proportion of Vietnamese consumers, especially students, participating in online shopping was still lower than in other countries in the region and around the world during the Covid translation According to Sylke et al (2002) in a number of other countries, e-commerce business-to-consumer is much lower than the

expected share of total retail enterprise due to its certain limitations Therefore, in order

to attract consumers, especially students who shop more online, it is very necessary to know the factors that affect the shopping behavior of customers online That is why I chose the topic “Factors affecting online shopping behavior of Banking University students during the Covid 19 pandemic” as the research topic From the research results, the author will give detailed explanations about the factors affecting online shopping behavior of Banking students during the Covid 19 translation, and at the same time find solutions to help sellers Online retail is closer to shoppers

1.2 The urgency of the topic

A recent Nielsen survey released at the Online Marketing Forum 2020 showed that the number of consumers shopping online increased by 25%, while in traditional channels such as supermarkets, markets and groceries only increased 7%, 3% and 6% respectively Ms Le Minh Trang, representative of Nielsen Vietnam Company, assessed that the online shopping trend in Covid-19 has opened up more online business opportunities when people choose to shop at home increased Online shopping has a 2-digit annual growth rate and this number is likely to grow in Vietnam Due to the COVID-19 pandemic, world trade and trade, education and other activities were disrupted The global supply chain has been broken because the countries are locked As

a developing country, Vietnam has suffered parallels by this outbreak Therefore, this research is designed to help online retailers have more overview of their customers, from which more solutions to attract customers through online shopping sites, especially during Covid translation This study is also essential to evaluate overall factors affecting online shopping behavior of students, to help them increase awareness of their own shopping behavior Although there are many theories and research models in the world that explain the factors affecting the behavior of online shoppers, there are not many specific studies in the country about the factors that affect the behavior of online shoppers Factors affecting online shopping behavior of consumers, especially the

student segment during Covid translation time 19 Models around the world when applied to Vietnam will not be appropriate due to the culture, economy, society Therefore, based on the models in the world and the studies in the country over the past time, building a model suitable with the situation of Vietnam is essential

1.3 Research objectives

- General objective

Find out the factors that influence students' online shopping behavior during the outbreak and the impact of each of these factors, and contribute to the research team's opinion on researchers' solutions, providing online shopping services to attract customers during the Covid 19 pandemic

- Contribute solutions for service providers to purchase online and attract more customers during the Covid 19 pandemic

- What improvements or changes are needed from online shopping service providers

to attract student customers to use?

1.5 Research object and Research scope

- Research object

Study subjects are factors affecting online shopping behaviors of Banking University students in Ho Chi Minh City during Covid 19 Subjects selected for the survey are Banking University students This is a young audience, knowledgeable about online shopping, so their buying behavior to a certain extent can represent all types of consumers in society The study period is from March 2020 to March 2021

- Research scope

- Scope of space: Research conducted at Banking University of Ho Chi Minh City

- Scope of time: Secondary data from 2020-2021, primary data taken from survey samples during February 2021 to March 2021

- Second, "students of Banking University of Ho Chi Minh City" are those who have been using online shopping regularly

Qualitative research: to explore the factors affecting online shopping behavior of students during Covid time and adjust the scale of the factors in the proposed research model Qualitative research results serve as a basis for questionnaires to collect information to perform quantitative research

Quantitative research: used to measure the influence of these factors on students' online shopping behavior during Covid time

- Evaluate the reliability of the scales by testing Cronbach's Alpha

- Analysis of discovery factors EFA by KMO test

Regression analysis and testing hypotheses with F and Sig tests

- T-Test and ANOVA test to find out significant differences in online shopping behavior among student customers

- Using SPSS

1.7 Research content

Research on consumer behavior of the student segment of the Banking University of Ho Chi Minh City with online shopping including cultural, social, personal, psychological, and customer purchasing decision-making process From there, evaluate the online shopping form during the epidemic, with the shopping demand for this segment, see if there is any change compared to before the Covid outbreak 19 The study will use the theory and empirical research by domestic and foreign authors who have done research

on online shopping behavior in general, to have analysis and understanding of this issue for the student segment From the results obtained during the research process, the author will give an explanation of the factors affecting online shopping behavior of Ho Chi Minh City Banking University students during Covid 19 and give their opinion The author's solutions to attract users to shop online during the pandemic

1.8 Research contribution

- In theory

Buying online is no longer a new field in Vietnam, but when buying goods during Covid

19 there is a difference The topic contributes a different perspective and more overview

in the field of online shopping during the pandemic, through building a theoretical model explaining the factors affecting the online buying behavior of students The scales in the proposed research model were implemented in India, Iran, Bangladesh ., this study adjusted and tested the scales in the Vietnamese environment through survey data experiment at Banking University, should contribute to research and application in the Vietnamese market Therefore, in addition to inheriting the previous studies, this research will provide a clear solution for online retailers to compete most effectively during Covid 19

1.9 Structure of research

Chapter 1: General overview

Introducing an overview of the topic, this chapter includes main contents such as research reasons, research questions and objectives, research scope and object, and research methods

Chapter 2: Literature review

CHAPTER 2: LITERATURE REVIEW

2.1 Basic Concepts

2.1.1 Online shopping concept

Online shopping is a form of commerce and electronics that allows customers to buy products or services directly from sellers over the internet Online shopping is one of the forms of e-commerce, becoming increasingly important in developing B2C e-commerce since the late twentieth century Online shopping is defined as a service where consumers use electronic devices with an Internet connection to make purchases (Turban et al., 2006) Online shopping encompasses a wide range of social changes, markets that are characterized by globalization, and the shift of the current economy based on knowledge, information, and technology in life Every day, some businesses have taken advantage

of online sales instead of traditional sales, which will help them reduce transaction costs, search, develop a broader market, and reduce the gap between buyers and sellers Monsuwe, Dallaert, and Ruyter (2004) have compared both offline and online and found that shopping online is more accessible than shopping offline, which takes less time and effort In addition, consumers can access more information related to products and services, helping them compare prices and product quality with other manufacturers In general, customers can easily receive any data and information from the internet (Wang,

Ye, Zhang & Nguyen, 2005) When shopping online, consumers cannot touch and feel

a product before buying, but online services provide more information about their products and services so that the customer can rate the products and services when they need it (Lim & Dubinsky, 2004)

2.1.2 Concept of consumer behavior

Consumer behavior refers to consumers' behavior in purchasing, using, evaluating, and rejecting products and services that consumers expect will satisfy their needs Consumer behavior focuses on whether with existing resources (time, money, effort), the individual will decide how to use them on the consumption of relevant items It includes what they

buy, why, when to buy, where, how often they buy them, how often they use them, how they are assessed after purchase, how these ratings affect those next purchase, and how they dispose of them

Consumer behavior involves both aspects: the mental decisions (thoughts) and the physical actions of the body created from those decisions/thoughts Consumers are those who buy and/or use products or services provided in the market Consumers are generally divided into two basic groups: personal consumers and organizational consumers Personal consumers are those who buy goods or services for their purposes (e.g., brushes, combs .), for families (e.g., television, table .), for relatives (lipstick , clothes…), friends (gift) These consumers are also referred to as end-users/ultimate consumers Institutional consumers include business organizations (enterprises), administrative and non-business units, They are the buyers of products and services for the operation of agencies and organizations In consumer behavior research, the focus is usually on individual consumers since end consumption is the factor that covers all the different types of consumer behavior and is relevant to all person as a buyer, consumer, or both

2.1.3 Consumer decision-making process

Researchers have found that consumers seem motivated and influenced by family, friends, and advertising when buying products/services and are affected by mood, circumstances, and feelings These factors combine to form a general, comprehensive model of consumer behavior, which both reflects the cognitive side and the emotional side of the consumer decision-making process

The consumer decision-making process consists of three phases: the input phase, the processing stage, and the output stage The input stage influences consumers' perceptions

of product needs, including two primary sources of information: the company's marketing efforts (products, pricing, promotions, and distribution channels) and factors External social factors impact consumers (family, friends, neighbors, culture, and subculture) The processing phase focuses on consumer decisions like How the

individual psychological factors (motivation, perception, education, personality, opinion) affect the output factors influenceaffect consumers' perception of need information, seek information before purchasing and reevaluate how the selection process is Experience gained through evaluating choices will, in turn, affect the inherent psychological attributes of consumers The output stage consists of two activities that are closely related: purchasing behavior and post-purchase evaluation Buying behavior for low-cost, non-permanent products can be influenced by manufacturer promotions and possibly a trial purchase if the consumer feels satisfied, maybe they will come back

to buy again continued The trial is the stage of surveying how consumers are judging

by using a product directly The act of returning to buy a customer's product proves that the consumer has accepted it For products that are relatively durable such as laptops (which are relatively durable due to quickly becoming out of date) signal acceptance Researchers have found that when buying products/services, consumers seem motivated and not only influenced by family, friends, advertising, but also influenced by mood, circumstances, feelings All of these factors combine to form a general, comprehensive model of consumer behavior, which both reflects the cognitive side and the emotional side of the consumer decision-making process

The consumer decision-making process consists of three phases: the input phase, the processing stage, and the output stage The input stage influences consumers' perceptions

of product needs, including two main sources of information: the company's marketing efforts (products, pricing, promotions and distribution channels) and factors external social factors impact on consumers (family, friends, neighbors, culture and subculture) The processing phase focuses on consumer decisions like How the individual psychological factors (motivation, perception, education, personality, opinion) affect the output factors affect consumers' perception of need information, seek information before purchasing, and reevaluate how the selection process is Experience gained through evaluating choices will in turn affect the inherent psychological attributes of

consumers The output stage consists of two activities that are closely related: purchasing behavior and post-purchase evaluation Buying behavior for low-cost, non-permanent products can be influenced by manufacturer promotions and possibly a trial purchase if the consumer feels satisfied, maybe they will come back to buy again The trial is the stage of surveying how consumers are judging by using a product directly The act of returning to buy a customer's product proves that the consumer has accepted it For products that are relatively durable such as laptops (which are relatively durable due to quickly becoming out of date) signal acceptance

2.2 General theories and research models of consumer behavior

2.2.1 Theory of Reasoned Action – TRA

The theory of reasoned action (TRA), developed by Fishbein and Ajzen, is one of the most influential theories used to explain human behavior According to this theory, behavioral intent can be explained by attitudes towards behavior and subjective norms, designed to explain behavior in general Attitudes towards behavior are defined as an individual's "positive or negative feelings (performance evaluation)" about the performance of the target behavior "(Fishbein and Ajzen, 1975)

Studies over the decades show that attitudes do not predict much of behavior Vicker (1969) concludes, "in general, attitudes do not appear to be related or weakly related to behavior" From the results of these studies, Fishbein and Ajzen (1980) discovered the method of predicting behavior from their reasoned action theory (TRA) attitudes and concluded that it is not attitude but rather planned behavior is a predictor of behavior Behavioral Intention (I) is the most crucial factor determining a person's behavior This intent is defined by Attitude (A) for the performance of the behavior and the Subjective Norms (SN) related to the behavior The Intent is seen as the closest and most important predictor of behavior, and it is influenced by attitudes and subjective norms

Model 1: Theory of Reasoned Action - TRA

(Source: Fishbein & Ajzen, 1975)

2.2.2 Theory of Planned Behavior – TPB

Theory of Planned Behavior (TPB) of Ajzen 1991 is the development and improvement from the rational action theory model (Fishein & Ajzen, 1975) According to planned behavioral theory, attitudes, subjective norms, and perceptions of behavioral control influence a consumer's intent to act Compared with TRA, the TPB model adds a cognitive factor that controls behavior affecting behavioral intention In addition, the element of belief about facilitation involves the perception factor of behavioral control According to Bunchan (2005), behavioral theory with TPB was born to overcome this weakness

According to TPB, "behavioral intent" of customers is affected by "attitudes",

"subjective norms" and "perception of behavioral control" TPB has been widely accepted and used in studies to predict specific user intent and behavior of individuals The empirical studies have shown the suitability of this model in studying consumer behavior in the context of online shopping Hansen et al (2004) tested both TRA and TPB models, and the results showed that the TPB model explains customer behavior better than the TRA model Moreover, given the relevance of the research context in

Vietnam, several studies have shown that TPB is more suitable for predicting consumer online shopping intentions

Model 2: Theory of Planned Behavior – TP

Online shopping will directly affect users' attitudes towards online shopping, and their attitudes will have a significant impact on online buying behavior Online buyer attitudes

significantly and positively influence their online buying behavior (Ariff et al., 2014) The consumer's attitude towards engaging in behavior has been shown to be a strong predictor of behavior (Fishbein & Ajzen 1975) Attitude refers to online consumer acceptance as a shopping channel (Olson et al., 2001) Previous studies have shown that online shopping attitudes are an important predictor of online purchases (Yang et al., 2007)

is the only factor that influences consumers more in purchasing decision in most cases

To attract consumers, companies often offer competitive prices, launching multiple promotions for their products According to Andreti, Zhafira, Akmal, and Kumar (2013), most consumers go to convenience stores to buy goods because the price is reasonable and has a significant impact on customers Munusamy and Hoo (2008) find that the pricing strategy significantly influences the customer's motivation and the consumer's buying decision Consumers care about the price and consider the price when deciding

to buy a product

2.3.3 Subjective norms

Ajzen (1991) defines subjective norms as the perception of influencers who should or should not perform the behavior According to the theory of reasoned action - TRA (Azjen & Fishbein 1980), human behavior is formed from intention, based on consumer attitudes towards behavior and perception Consumer behavior is influenced by those around them, such as family, friends, co-workers, the media, and the influencers of buying behavior If they say good / bad about the product, it will affect the buying behavior of consumers Subjective standards can be described as the individual's

perception of social pressures for performing or not performing a behavior Previous studies have suggested that there is a positive relationship between subjective norms and intentions In the context of online shopping, Lin (2007) argued that subjective benchmarks reflect consumer perception of the group's influence on the ability to shop online

2.3.4 Perceived behavioral control

Perceived behavioral control is defined as an individual's perception of how easy or difficult it is to perform a certain behavior It denotes the degree of control over the behavior's performance, not the results of the behavior In the context of online shopping, behavioral control perceptions describe consumer perceptions of the availability of necessary resources, opportunities to make online shopping Perceived behavioral control has been shown to have a positive impact on consumers' online shopping intentions Perceptions of behavioral control reflect the perception of internal limitations (self-efficacy) as well as external limitations in behavior such as resources available Perceptions of behavioral control directly influence online shopping behavior (George 2004) and have a strong relationship with online shopping (Khalifa & Limayem 2003)

2.3.5 Perceived risk

According to Bauer (1960), risk-aware consumer behavior of IT products includes two factors: perception of risk related to products/services and perception of risk related to online transactions online The product/service-related risk perception component includes risk perceptions such as loss of functionality, financial loss, time consuming, and total risk perception with the product/service According to Pavlou (2003), the risks

in online shopping include economic risk, seller risk, privacy risk, and security risk Four criteria measure perception of risk: not receiving the product, difficulty to test actual products, unable to come into contact with the product, not pushing the product before purchasing Forsythe et al., 2006 Meanwhile, Corbitt et al (2003) argued that two criteria measure consumer risk perception in online shopping: financial risk and product risk -

product may not meet customer expectations The risk perception component related to online transactions is the risks that can occur when consumers perform e-commerce transactions on electronic devices related to security and safety - complete authentication and risk awareness about online transactions

2.4 Overview of research

2.4.1 Domestic research

- Factors affecting online shopping intentions of Vietnamese consumers: Expanded

research planning behavior theory ( Ha Ngoc Thang, 2016)

The study discusses the factors influencing Vietnamese consumers' online buying intentions based on the theory of planned behavior Questionnaires were sent directly via the Internet to the respondents in 5 months, with 423 valid responses to be analyzed Data are analyzed according to the process from factor analysis to reliability testing and regression analysis The results showed that attitudes and perceptions that control consumer behavior positively affect buying intentions online Meanwhile, perceived risk has a negative effect on consumers' intention to buy online

Model 3: Research model in research of Thang (2016)

- Analysis of factors affecting online shopping behavior of Can Tho city consumers (

Nguyen Thi Bao Chau and Le Xuan Dao, 2014)

The purpose of this study is to identify factors affecting online shopping behavior of Can Tho city consumers Data collected from 130 consumers (100 who shop online and 30 who do not shop online), using factor analysis, multivariate regression and differentiation to identify the factors affect online shopping behavior of Can Tho city people Research results have shown financial and product risk factors, variety of product selection, trust, web site responsiveness, time risk, comfort, convenience, Price affects a consumer's decision to continue (or start) shopping online In particular, the comfort factor has the greatest impact on online shopping behavior

Model 4: Research model in research of Chau & Dao (2012)

- Factors affecting online shopping intentions of customers in Vietnam ( Nguyen Le

This study uses the modified TAM model as the theoretical basis to build and develop a research model of factors affecting online shopping intentions Research is done by qualitative and quantitative methods The first is done through direct interviews with 5 subjects who have experience in online shopping for more than 2 years Respondents are young people, from 22-25 years old, most of them have experience in using the Internet and have knowledge of online shopping services Using quantitative survey questionnaires according to the convenient method, the results obtained 171 matching questionnaires The author used: test the scale (assess the reliability of Cronbach alpha and analyze the discovery factor EFA) Test hypotheses of the multivariate regression method performed on SPSS 20 Through research, the two components of perceiving the usefulness, the perception of ease of use, the components of the expected price and the reliability are all have the same effect on online shopping intentions Especially the Price Expectation component has a strong impact on online shopping intent Meanwhile, the perception of risk related to online transactions and the perception of risk related to the product / service has a negative impact on intent to use

2.4.2 Foreign research

- An Analysis of Factors Affecting on Online Shopping Behavior of Consumers

(Javadi, Dolatabadi, Nourbakhsh, Poursaeedi, và Asadollahi, 2012)

The purpose of this study is to analyze the factors that influence consumers' online shopping behavior The study uses a model to examine the impact of cognitive risk, infrastructure variables and return policy on subjective attitudes and norms, perceived behavioral control, innovation in particular areas and attitudes about online shopping behavior Respondents were online consumer stores in Iran who were randomly selected through 200 questionnaires scattered among online stores The author uses regression to analyze data, test the hypotheses of learning Research has determined that financial risks and non-delivery risks negatively affect online shopping attitudes The results also show that domain-specific innovation and subjective indicators positively affect shopping

behavior Moreover, online shopping attitudes positively influence consumers' online shopping behavior

Model 5: Research model in research of Javadi et al (2012)

- Factors Affecting Consumers’ Internet Shopping Behavior During the COVID-19

Pandemic: Evidence From Bangladesh (Neger and Uddin, 2020)

The research investigates product factors, price factors, time-saving factors, payment factors, security factors, administrative factors and psychological factors on shopping behavior Consumer internet during the coronavirus (COVID-19) pandemic in

Attitude

Subjective norms

Perceived behavioral control

Online shopping behavior

Bangladesh Data collected from 10 May 2020 to 10 June 2020 from 230 Bangladeshi online consumers Data were analyzed using descriptive statistical analysis, reliability analysis, and multivariate regression analysis The results showed that all factors except price and security were positively and significantly associated with consumers' internet shopping during the Covid 19 epidemic in Bangladesh

Model 6: Research model in research of Neger and Uddin (2020)

- Fluctuating Attitudes and Behaviors of Customers toward Online Shopping in Times

of Emergency: The Case of Kuwait during the COVID-19 Pandemic (Alhaimer, 2021)

This study investigates various risk factors that alter online shopping behavior in Kuwait during the COVID-19 pandemic Use online questionnaires distributed through multiplesocial networking platforms Overall, 385 responses were collected via online questionnaires and data analyzed using AMOS 21 for structural equation modeling purposes The results show that risk tolerance, the severity of the risk, and the risk of legal penalties positively affect consumers' online buying attitudes in Kuwait In contrast, product risk, financial risk, and non-delivery risk are not significantly affected The risk of convenience is the only factor that negatively affects attitudes Furthermore, the author found that the official penalties imposed on those who violated the door lock rule could have a direct and positive effect on consumer behavior towards online shopping in this era Translate Factors affecting users' attitudes and behavior toward online shopping during normal non-urgent times are different from factors during times

of emergency

2.4.3 Proposed research model

The research is based on Ajzen and Fishbein's Theory of Reasoned Action (1980), Theory of Planned Behavior (TPB) by Ajzen (1991) along with research articles referenced at home and abroad on online shopping behavior such as: Ha Ngoc Thang (2016), Nguyen Le Phuong Thanh (2013), Javadi et al (2012), Neger and Uddin (2020), Alhaimer (2021) This will serve as a basis for selecting and proposing an appropriate research model From the theoretical basis and summary of previous research results, the proposed research model includes five factors affecting online shopping behavior of Banking University students during the Covid-19 period including: These include: (1) Attitude, (2) Price, (3) Subjective Norms, (4) Perceived behavioral control, (5) Perceived risk

The research hypothesis

H1 : Attitude has a positive impact on online shopping behavior of students during Covid H2 : Price has a negative impact on online shopping behavior of students during Covid H3 : Subjective Norms have a positive impact on online shopping behavior of students during Covid

H4 : Perceived behavioral control has a positive impact on online shopping behavior of students during Covid

H5 : Perceived Risk has a negative impact on online shopping behavior of students during Covid

Model 7: Research model

CHAPTER 3: METHODOLOGY

3.1 Research design

In the research design section, the authors will mention how to build a scale, select a

sample, collect tools, and collect information

3.1.1 Method of building a scale

The study has 2 research objectives related to the establishment of the scale, including:

- Measuring the characteristics of students participating in the study from the perspective of being an interviewee

- Ask participants to rate the level of agreement with the main factors affecting students' online shopping behavior during the Covid epidemic

Nominal scale is built to distinguish and identify research objects The topic has built nominal scales including: Gender, School year, School of study, Income, How long have you been using the Internet, How many hours do you use the Internet in a day, Shopping sites often buy during the Covid pandemic, products often purchased by participants The advantage of this scale is that it is easy to set up as well as highly specific and provides useful information

The hierarchical scale is built to quantify and arrange problems in order, to measure attitudes, consciousness, opinions, interests and perceptions The scales and observations

in the topic use the Likert scale (5 levels) and are described in detail in a table to identify the main factors affecting the decision to choose a foreign language center of the students student

The model has 5 scales of independent factors (with 25 observed variables) and a scale

of dependent factors (with 5 observed variables) built on a theoretical basis

Hypothesis H0 has 5 factors including: Attitude factor, Price factor, Subjective norms factor, Perceived behavioral control factor, Perceived risk factor

The dependent factor is the online shopping behavior of students at Banking University

of Ho Chi Minh City during Covid

3.1.2 Research scale

Data sources include primary and secondary data

Primary data was collected through surveys and interviews The entire study was conducted using survey questionnaires because it was easier for respondents to complete the questionnaire The questionnaire was posted to student groups of Banking University

of Ho Chi Minh City The responses from students obtained through the questionnaire will be recorded through the researcher's email address

Secondary data is collected from external sources such as books, journals, research articles and internet databases to provide information on theoretical foundations, research models, research methods, the scale…

The scales built in the article:

Attitude Scale

The scale for the Attitude variable in this study is referenced from the scale in the study

of Samar, S., M Ghani, and F Alnaser (2017); Rahi, S., M Ghani, and A Ngah (2018)

A1 I find online shopping to be worth using,

especially during Covid's time Samar, S., M Ghani, and

F Alnaser (2017) A2 I think that online shopping during Covid has

brought many new experiences

A3 I found it wise to shop online during Covid's

The scale for the Price variable in this study is referenced from the scale in the study

of Cheong and Park (2005) ; Tinne, Wahida Shahan (2011)

P1 I think online shopping is expensive

Cheong and Park ( 2005 )

P2 I am willing to use online shopping even

though the price is high

P3

Shipping price is my main consideration

when deciding to use or not to use online

shopping services

P4 Price is the key factor in online shopping

P5 Choose products with affordable prices

when shopping online

Tinne, Wahida Shahan (2011)

Hypothesis H2 : Price has a negative impact on online shopping behavior of students during Covid

Subjective Norms Scale

The scale for the Subjective Norms variable in this study is referenced from the scale in the study of Nguyen Ngoc Tram (2015) ; Rehman and Ayoup (2019)

Symbol The scale Source

SN1 Your opinion is important to me when

shopping online

Nguyen Ngoc Tram (2015) SN2

I would have no problem shopping online

if my friends and relatives bought it

without problems

SN3 Sharing experiences through product

reviews will catch my attention

SN4 I shop online because I can get details

about products online

Rehman and Ayoup (2019)

SN5 I shop online because I can shop

whenever I want

Hypothesis H3 : Subjective Norms have a positive impact on online shopping behavior of students during Covid

Perceived behavioral control Scale

The scale for the Perceived behavioral control variable in this study is referenced from the scale in the study of Nguyen Ngoc Tram (2015) ; Hsu and Chang (2006)

PBC 1 I don't shop online without a home

PBC 3 I don't shop online because the network

speed is very slow

PBC 4 Whether I use online shopping or not is

entirely up to me

Hsu and Chang (2006)

PBC 5 I feel like I can control my spending when

I shop online

Hypothesis H4 : Perceived behavioral control has a positive impact on online shopping behavior of students during Covid

Perceived Risk Scale

The scale for the Perceived Risk variable in this study is referenced from the scale in the study by Javidi et al (2012) ; Featherman and Pavlou (2003)

PR1 I feel that my credit card information could be

compromised and misused if I shop online

Javidi et al (2012) PR2

I feel that my personal information providing

to deal with retailers may be compromised to

third parties

PR3

I might be overcharged if I shop online

because the retailer has my credit card

information

PR4

When transferring money online, I am afraid

that I will lose money due to careless errors

such as wrong account number or wrong

amount

Featherman and Pavlou (2003)

PR5 When a transaction error occurs, I am worried

that I cannot get a refund from the seller

Hypothesis H5 : Perceived Risk has a negative impact on online shopping behavior of students during Covid

Online shopping behavior scale

The scale for the Online shopping behavior variable in this study is referenced from the scale in the study of Nguyen Ngoc Tram (2015) ; Huang et al (2013)

Symbol The scale Source

OSB 1 Online shopping makes it easier for me to

shop during social breaks

Nguyen Ngoc Tram

(2015) OSB 2 I have more choices when I shop online

OSB 3 I can shop whenever I want

OSB 4 I can avoid crowds when shopping online

during Covid time OSB 5 I will continue to shop online in the future Huang et al (2013)

Summary of the scales in the research model

Table 3 1 Summary of scale

3 I found it wise to shop online during Covid's time

4 Online shopping during Covid becomes my habit

5 Shopping online during Covid's time was fun and enjoyable

II Price

6 I think online shopping is expensive

7 I am willing to use online shopping even though the price is high

8 Shipping price is my main consideration when deciding to use or not

to use online shopping services

9 Price is the key factor in online shopping

10 Choose products with affordable prices when shopping online

III Subjective norms

11 Your opinion is important to me when shopping online

12 I would have no problem shopping online if my friends and relatives

bought it without problems

13 Sharing experiences through product reviews will catch my attention

14 I shop online because I can get details about products online

15 I shop online because I can shop whenever I want

IV Perceived behavioral control

16 I don't shop online without a home computer

17 I don't shop online if I don't have a credit card

18 I don't shop online because the network speed is very slow

19 Whether I use online shopping or not is entirely up to me

20 I feel like I can control my spending when I shop online

V Perceived risk

21 I feel that my credit card information could be compromised and

misused if I shop online

22 I feel that my personal information providing to deal with retailers

may be compromised to third parties

23 I might be overcharged if I shop online because the retailer has my

credit card information