factors affecting online shopping behavior of consumers in hanoi

FOREIGN TRADE UNIVERSITY FACULTY OF INTERNATIONAL ECONOMICS -*** - RESEARCH PROPOSAL Research topic: Factors affecting online shopping behavior of consumers in Hanoi Class: KTEE206(GD1-HK1-2223).1 Instructor: Prof Pham Thi Cam Anh Hanoi, 2022 TABLE OF CONTENTS TABLE OF CONTENTS Introduction 1.1 Research topic 1.2 The reason for choosing the topic 1.3 Research objectives 1.3.1 General objectives 1.3.2 Specific goals 1.4 Subjects and scope of study 1.5 Research Questions 1.6 Overview of the previous research situation Literature review and theoretical framework 2.1 Literature review 2.1.1 Domestic research 2.1.2 Foreign research 2.2 Foundational theoretical studies related to research questions 2.2.1 Theoretical research concept 2.2.2 Theoretical research model 10 2.3 Proposing a research model 12 Research process and methods 14 3.1 Research process 14 3.2 Research samples and data collection methods 14 3.3 Data processing methods .15 3.3.1 Cronbach's Alpha Reliability Test 15 3.3.2 Discovery Factor Analysis (EFA) 15 3.3.3 Pearson Correlation Analysis 16 3.3.4 Regression analysis .16 Access to research topics 16 4.1 Approach to the topic 16 4.2 Summary of research problem and model proposal 17 4.3 Propose future research ideas .17 4.4 Implications for management practices or policies .18 References .19 Introduction 1.1 Research topic Factors affecting online shopping behavior of consumers in Hanoi 1.2 The reason for choosing the topic Online shopping is growing rapidly in Vietnam, especially in the period of 2016-2020 [ CITATION Nhi21 \l 1033 ] The average growth rate of e-commerce in Vietnam is about 30% (up from billion USD in 2015 to about 11.5 billion USD in 2021[ CITATION Hiệ22 \l 1033 ] In which, the online retail sector increased by 46%, ride-hailing and technology food increased by 34%, marketing, entertainment and online games increased by 18%, particularly the online tourism sector decreased by 28% [ CITATION DPD22 \l 1033 ] With the current rapid development rate, researchers and e-commerce businesses need to have appropriate policies to attract customers to buy on their ecommerce sites It is necessary to have an academic, general study of the customer's purchasing decision process to propose appropriate solutions Given the importance of research on online shopping decisions, the authors chose the topic "Factors affecting online shopping behavior of consumers in Hanoi" as the topic of research on their subject topic Thereby it is possible to systematize research theories about consumers' online shopping decisions, proposing research models Thereby creating a premise and further research orientation for future studies 1.3 Research objectives 1.3.1 General objectives The overall goal of the topic is to find out factors affecting online shopping behavior of consumers in Hanoi From there, the research will offer solutions to help businesses build a suitable plan to improve business efficiency 1.3.2 Specific goals The topic sets out the specific research objectives as follows: Firstly, identify Factors affecting online shopping behavior of consumers in Hanoi Second, measure the impact of factors affecting consumers' online shopping behavior in Hanoi Third, verify the differences of the research model and validate the entire theoretical model, thereby adding the theory and proposing management implications for managers to develop and attract customers in Hanoi for online products 1.4 Subjects and scope of study Subjects of study: Factors affecting online shopping behavior for consumers in Hanoi Survey subjects: Consumers in Hanoi 1.5 Research Questions 1/ What factors affect the online shopping behavior of consumers in Hanoi? 2/ What is the impact of factors affecting online shopping consumers in Hanoi? behavior for 3/ What governance implications are proposed for managers in developing and attracting customers in Hanoi for online products? 1.6 Overview of the previous research situation Studies on the problem of online buying behavior have been of interest to researchers for a long time The most recent in Vietnam is the study by authors Ta Van Thanh and Dang Xuan On [CITATION Thà21 \n \t \l 1033 ] with the topic "Factors affecting the online shopping intentions of Generation Z consumers in Vietnam"; research by Nguyen Minh Tuan and Nguyen Van Anh Vu [CITATION Tuấ20 \n \t \l 1033 ]“Factors that impact customers' online buying behavior at TIKI VN"; research by Ha Ngoc Thang and Nguyen Thanh Do[CITATION Thắ16 \n \t \l 1033 ] "Factors affecting vietnamese consumers' online shopping intentions: An extended study of planned behavior theory" Overseas studies such as: Anum Tariq et al.[CITATION Tar16 \n \t \l 1033 ] "Factors Affecting Consumers' Online Shopping Behavior in Pakistan"; Kok Wai Tham et al [CITATION Das19 \n \t \l 1033 ] "Perceived risk factors affecting consumers' online shopping behavior"; Meher Neger and Burhan Uddin [CITATION Neg20 \n \t \l 1033 ] "Factors Influencing Consumers' Internet Shopping Behavior during the COVID-19 Pandemic: Evidence from Bangladesh" These studies have confirmed model theories of behavior and technology adoption that are applicable in the case of studying factors that influence consumers' online shopping behavior Literature review and theoretical framework 2.1 Literature review 2.1.1 Domestic research 2.1.1.1 Research by Ha Ngoc Thang and Nguyen Thanh Do (2016) Authors Ha Ngoc Thang and Nguyen Thanh Do (2016) had the topic "Factors affecting online shopping intention of Vietnamese consumers: Research to expand the theory of planned behavior" with the goal of exploring the effects of factors on the online purchase intention of Vietnamese consumers based on the theory of planned behavior Results based on 423 observed samples by regression analysis method show that consumers' attitude and perception of behavioral control have a positive influence on online purchase intention Perceived risk factor has a negative effect on consumers' intention to buy online Figure 2.1 Research model of Ha Ngoc Thang and Nguyen Thanh Do Source: Ha Ngoc Thang and Nguyen Thanh Do (2016) 2.1.1.2 Research by Nguyen Minh Tuan and Nguyen Van Anh Vu (2020) Nguyen Minh Tuan and Nguyen Van Anh Vu (2020) studied the topic "Factors affecting online shopping behavior of customers at TIKI.VN" With the aim of discovering the factors affecting the online purchase behavior of customers at TIKI.VN, with 300 research samples, the authors used the regression method to test the relationships Finally, the results showed that factors affect the online purchasing behavior of customers at Tiki.vn: Perceived ease of use, Useful perception, Reliability, Social factors, Risk perception and Enjoyment Figure 2.2 Research model of Nguyen Minh Tuan and Nguyen Van Anh Vu Source: Nguyen Minh Tuan and Nguyen Van Anh Vu (2020) 2.1.1.3 Research by Ta Van Thanh and Dang Xuan On (2021) Ta Van Thanh and Dang Xuan On (2021) researched "Factors affecting online shopping intention of Generation Z consumers in Vietnam" to assess the factors affecting shopping intention of Generation Z online consumers in Vietnam The author studied 600 observed samples in Vietnam The methods of scale analysis, model evaluation, regression, etc were applied in this study The results showed factors: Perceived usefulness, Trust, Perceived risk and Psychological safety that affect the online shopping intention of Generation Z Figure 2.3 Research model of Ta Van Thanh and Dang Xuan On Source: Ta Van Thanh and Dang Xuan On [CITATION Thà21 \n \t \l 1033 ] 2.1.2 Foreign research 2.1.2.1 Research by Anum Tariq et al (2016) Anum Tariq et al (2016) with the study "Factors affecting online shopping behavior of consumers in Pakistan" The study aimed to evaluate the factors affecting the online shopping behavior of Pakistani consumers The results showed that there are factors affecting online purchase behavior including: Convenience, Financial risk, Product risk, Risk of non-delivery and Return policy Figure 2.4 Research model of Anum Tariq et al Source: Anum Tariq et al (2016) 2.1.2.2 Research by Kok Wai Tham et al (2019) Author Kok Wai Tham et al (2019) has the topic "Perceived Risk Factors Affecting Consumers' Online Shopping Behaviour" research, aimed to assess the impact of risk factors on consumers' online shopping behavior in Malaysia In the study, the author used the regression method with 245 research samples Research shows that product risk, convenience risk, and return policy risk have a positive and significant impact on online shopping behavior Financial risk was found to have a negative and negligible impact on consumer behavior In addition, non-delivery risk was found to have a significant and negative impact on online shopping behavior Figure 2.5 Research model of Kok Wai Tham et al Source: Kok Wai Tham et al (2019) 2.1.2.3 Research by Meher Neger and Burhan Uddin (2020) Meher Neger and Burhan Uddin (2020) published a study with the title "Factors Affecting Consumers' Internet shopping behavior during the COVID-19 pandemic: Evidence from Bangladesh (Factors Affecting Consumers' Internet) Shopping Behavior During the COVID-19 Pandemic: Evidence From Bangladesh)” The objective of this study is to evaluate the factors affecting the online shopping behavior of consumers in Bangladesh in the context of the Covid-19 pandemic The study collected data from May 10, 2020 to June 10, 2020 in a personal interview using an online survey method through a structured questionnaire with a five-point Likert scale from 230 people Bangladeshi online consumption Non-probability sampling method was used Data were analyzed using descriptive statistics, reliability analysis, and multiple regression analysis The results show that all factors except price and security have a positive and significant relationship with consumers' internet shopping behavior during the coronavirus (COVID-19) pandemic ) in Bangladesh Figure 2.6 Research model of Meher Neger and Burhan Uddin Source: Meher Neger Burhan Uddin [CITATION Neg20 \n \t \l 1033 ] 2.2 Foundational theoretical studies related to research questions 2.2.1 Theoretical research concept 2.2.1.1 Consumer concept There are many concepts of the consumer, one of the most popular of which is that of Philip Kotler and Gary Armstrong.[CITATION Kot121 \n \t \l 1033 ] "The consumer is the audience that the business serves and is the determining factor in the success or failure of the business." According to the Law on Protection of Consumer Interests 2010: "Consumers are buyers and users of goods and services for the purposes of consumption and activities of individuals, families and organizations"[ CITATION Quố10 \l 1033 ] Consumers are individuals or organizations that businesses are making marketing efforts towards They are the ones making the shopping decisions Consumers are the beneficiaries of the quality characteristics of products and services[ CITATION Riz01 \l 1033 ] 2.2.1.2 The concept of consumer behavior Consumer behavior is the activities of consumers in shopping and using products/services This includes identifying needs, seeking information, evaluating alternatives, buying decisions, and post-purchase behavior [CITATION Kot03 \l 1033 ] Theo Philip Kotler [CITATION Kot121 \n \t \l 1033 ], consumer behavior is the behavior of individual consumers when making decisions about the purchase, use and cancellation of products or services Consumer behavior is behavior that manifests itself in the actions of searching, purchasing, using, or counterfeiting products/services expected by consumers to satisfy their needs [ CITATION Pre09 \l 1033 ] 2.2.1.3 The concept of behavioral intent Intent is a factor used to evaluate your ability to perform future behaviors [ CITATION Sol14 \l 1033 ] Theo Ajzen [CITATION Ajz91 \n \t \l 1033 ], intention is a motivating factor, motivating the individual to be ready to perform the behavior Behavioral intentions are made up of three factors including attitudes towards behavior, subjective norms, and behavioral control [ CITATION Ajz80 \l 1033 ] In it, attitude is "an individual's assessment of the results obtained from the performance of a behavior"[ CITATION Ajz91 \l 1033 ] It can be said that behavioral intent measures the subject's ability to perform behavior subjectively… 2.2.1.4 The concept of consumer online shopping intent Anum Tariq et al (2016) argue that "online shopping intent is the ability of consumers to make purchases through an online environment." According to Cai and Cude (2016), a consumer's online shopping intent is a consumer's ability to perform internet shopping behavior The goal of online shopping is the ability of consumers to make purchases over the Internet (Delafrooz & Paim, 2011) 2.2.1.5 The concept of consumer online shopping behavior Online shopping behavior (also known as Internet shopping behavior) describes the behavior of a consumer's purchase of products or services through the Internet (Ha & Stoel, 2009) According to Hashim Shahzad (2015) online shopping behavior by consumers is the activity of shopping through online stores on the Internet or online shopping websites 2.2.2 Theoretical research model 2.2.2.1 Rational Action Theory (TRA) The Theory of Reasoned Action defines the relationship between attitude and behavior in human actions (Ajzen & Fishbein, 1980) Rational action theory is used to predict behavior based on a person's inherent attitudes and behavioral intentions A person will act based on the results they expect when performing the behavior (Vallerand, et al., 1992) Figure 2.7 Rational Action Theory (TRA) Model Source: Ajzen & Fishbein (1980) From the studies of social psychology, models and theories of persuasion, attitudes Psychology researchers Martin Fishbein and Icek Ajzen have developed the rational action theory (TRA) model, which shows that there is a relationship between attitudes towards behavior, subjective norms that influence behavioral intentions and have an impact on human behavior (Ajzen & Fishbein, 1980) However, rational action theory is not a complete theory for analyzing human behavior (Cooke & French, 2008) According to Ajzen (1991) there is uncertainty about performing the act according to intention The limitations of the theory range from the assumption that behavior is under the control of the will, the fact that behavior is not necessarily carried out from existing intentions, another limitation is that attitudes and behaviors sometimes have no connection with intentions Therefore, rational action theory can only be applied to pre-intended behaviors, this theoretical model cannot be applied to unconscious habits and actions, (Ajzen, 1991) In subsequent studies, Martin Fishbein and Icek Ajzen worked on overcoming the limitations of rational action theory 2.2.2.2 Planned Behavior Theory (TPB) The Theory of Planning Behaviour is a theory that defines the relationship between a person's beliefs and behavior (Ajzen, 1991) Planned behavior theory is extended from the rational action theory (Ajzen & Fishbein, 1980) According to Ajzen (1991), planned behavior theory aims to improve the theoretical model of rational action by adding to the cognitive factor model that controls behavior, overcoming the limitation that human behavior is completely controlled by reason 10 Planned behavior theory is the most applied and cited in terms of behavior theory (Cooke & Sheeran, 2004), applied to many different fields of study such as marketing, sports, health, Figure 2.8 Planned Behavior Theory Model (TPB) Source: Ajzen (1991) The planned behavior theory model assumes that behavior can be predicted or explained by the intentions of performing that behavior According to Ajzen (1991), intention is a function of factors: Attitude toward the Behavior; Subjective Norms; and Perceived Behavioral Control 2.2.2.3 Technology Acceptance Model Theory (TAM) Technology Acceptance Model Theory (TAM) focuses on explaining the technology acceptance behavior of users (Davis, 1989) The model assumes that users of technology products, in addition to their attitude, the performance that technology products bring will also affect their ability to accept that technology product is very high (Davis, 1989) Figure 2.9 Technology Acceptance Theoretical Model (TAM) Source: Davis (1989) 11 The Technology Acceptance Model (TAM) is the most used and most influential model (Marangunic & Granic, 2015) The two main factors that influence technology use behavior are perceived usefulness and perceived ease of use Davis (1989) argues that the behavior of using technology is based on the intention to use, on the other hand, the intention to use is determined by the attitude when using and the perception of the user 2.3 Proposing a research model Summary of some research results on factors affecting consumers' online shopping behavior Table 2.1 Summary of some research results on factors affecting consumers' online shopping behavior N o Factor Source Attitude Ha Ngoc Thang and Nguyen Thanh Do (2016) Opinion of the reference group Ha Ngoc Thang and Nguyen Thanh Do (2016) Cognitive behavioral control Ha Ngoc Thang and Nguyen Thanh Do (2016) Perceived risk Ha Ngoc Thang and Nguyen Thanh Do (2016) Awareness Nguyen Minh Tuan and Nguyen Van Anh Vu (2020) The enjoyment Nguyen Minh Tuan and Nguyen Van Anh Vu (2020) Risk perception Nguyen Minh Tuan and Nguyen Van Anh Vu (2020) Social factors Nguyen Minh Tuan and Nguyen Van Anh Vu (2020) Reliability Nguyen Minh Tuan and Nguyen Van Anh Vu (2020) Perceived ease of use Nguyen Minh Tuan and Nguyen Van Anh Vu (2020) 10 11 Useful Ta Van Thanh and Dang Xuan On (2021) 12 Reputation Ta Van Thanh and Dang Xuan On (2021) 13 Risk Ta Van Thanh and Dang Xuan On (2021) 14 Reference group Ta Van Thanh and Dang Xuan On (2021) 15 Safe Ta Van Thanh and Dang Xuan On (2021) 12 16 Convenience Anum Tariq et al (2016) Financial risk Anum Tariq et al (2016) 17 18 Product risk 19 Risk of non-delivery Kok Wai Tham et al (2019)) Anum Tariq et al (2016) Kok Wai Tham et al 2019) Anum Tariq et al (2016) Kok Wai Tham et al (2019) 20 Return Policy Anum Tariq et al 2016) 21 Convenience risks Kok Wai Tham et al (2019)) 22 Return policy risk Kok Wai Tham et al 2019) 23 Product Meher Neger and Burhan Uddin (2020) 24 Price Meher Neger and Burhan Uddin (2020) 25 Save time Meher Neger and Burhan Uddin (2020) 26 Abate Meher Neger and Burhan Uddin (2020) 27 Security Meher Neger and Burhan Uddin (2020) 28 Administrative Meher Neger and Burhan Uddin (2020) 29 Psychology Meher Neger and Burhan Uddin (2020) Source: General Author Along with these factors, the authors also rely on the rational action theory (TRA) and technology acceptance model (TAM) to build a research model applied to the case of online shopping of consumers in Vietnam as follows: 13 Figure 2.10 Proposed research model Source: Author synthesis and recommendations Research process and methods 3.1 Research process In order to ensure the science of his topic, this research is carried out through steps Each step ensures the objective and general nature of the topic Specifically, the steps are presented in the section below: Overview Research issues The urgency of the topic Research objectives and questions Subjects and scope of study Conclusions and recommendations Suggest solutions Further research orientation Theoretical basis Purchase behavior Online shopping behavior Theoretical research model Research Overview Quantitative research Descriptive statistics Cronbach’s Alpha Discovery Factor Analysis (EFA) Pearson Correlation Analysis Regression analysis Check the suitability of the model T-Test Inspection ANOVA Accreditation Qualitative research Group discussions Build models and scales Models and scales Build a survey Sample size design, methods Figure 3.11 Research process Source: Author 3.2 Research samples and data collection methods How to determine the study sample size: According to Hair et al (2014), the minimum sample size to use the EFA method is 50, preferably 100 or more The ratio of the number of observations to an analytical variable is 5:1 or 10:1, some researchers suggest that this ratio should be 20:1 "Number of observations" is simply understood as the number of valid survey votes needed, "Measurement variable" is a measurement question in a survey 14 N = * Number of measurement variables participating in EFA Because the research uses existing research models conducted in foreign markets, the industry as well as the research area have a variety of users By the method of selecting survey subjects who have known and purchased skin care products to survey to collect data In this study, with a survey of 20 questions using the 5-degree Likert scale (corresponding to 20 observation variables of different factors), the author applied hair et al (2014) formula with a ratio of 5:1 Therefore, the sample size used in this study is 200 to ensure the minimum reliability for conducting data analysis 3.3 Data processing methods 3.3.1 Cronbach's Alpha Reliability Test The scales are evaluated for reliability through Cronbach's Alpha reliability factor of SPSS statistical software version 20.0 The scale used in this study will continue to be evaluated by Cronbach's Alpha confidence factor This coefficient was discovered in 1951, used to measure the reliability of the scale according to the intrinsically consistent method Cronbach's Alpha coefficient is calculated using the following formula: Where: k is the number of observed variables in the scale; σ i i s t h e va r ia n c e o f t h e i- th o bs e r v a t i o n va r ia b l e , is the variance of the total scale The scales used in the study included in the reliability test with Cronbach's Alpha coefficient of at least ≥ 0.6 are usable in the case of a new or new scale concept for respondents in the context of the study (Nunnally (1978); Peterson (1994); quoted by Hoang Trong and Chu Nguyen Mong Ngoc (2008) and Corrected Item-Total Correlation > 0.3 (Trong & Ngoc, 2005) 3.3.2 Discovery Factor Analysis (EFA) EFA discovery factor analysis method to verify the value convergence of the scale The KMO (Kaiser-Meyer-Olkin) coefficient must have a value of ≥ 0.5 Observable variables with factor loading ≤ 0.5 will be discarded The Eigenvalue stops >1 and the total quoted variance ≥ 50% (Trong & Ngoc, 2005) Factor analysis is performed through SPSS 20.0 for Windows statistical software with principal components analysis, Varimax procedure to minimize the number of variables with a large coefficient at the same factor, so will enhance the ability to explain the factors) and the stop when extracting the factor has an Eigenvalue of The KMO (Kaiser-Meyer-Olkin measure of sampling adequacy) is an indicator used to consider the appropriateness of factor analyses A large KMO value (between 0.5 and 1) means that factor analysis is appropriate, whereas if the KMO is less than 0.5, factor analysis is likely not appropriate for the data 15 3.3.3 Pearson Correlation Analysis The author uses the Pearson correlation coefficient to quantify how close the linear relationship between two quantitative variables is Before conducting a linear regression analysis, it is necessary to consider the correlation relationship between the dependent variable and each independent variable, as well as between the independent variables According to Hoang Trong and Chu Nguyen Mong Ngoc (2008), Pearson correlation coefficients are used to quantify how close the linear relationship between quantitative variables is Checking the dependent variable and the independent variable to see if they are correlated, the absolute value of the correlation coefficient (r) indicates how close the linear relationship is If the correlation coefficient between the dependent variable and the independent variable is greater (closer to 1), the closer the relationship between the variables is, if the positive correlation coefficient proves that the independent variable and the dependent variable are related in the direction, if the negative correlation coefficient proves that the independent variable and the dependent variable are oppositely related The value of r indicating that there is no linear relationship between the two variables does not necessarily mean that the two variables have no relationship Therefore the linear correlation coefficient should only be used to denote the degree of tightness of the linear correlation relation (Trong, 2008) If two variables are correlated, then there is a Pearson correlation coefficient │r│ > 0.1 Testing between two independently correlated variables does not leave the multi-linear problem in regression analysis 3.3.4 Regression analysis In order to identify, measure and evaluate the influence of the groups of factors obtained from the discovery factor analysis (EFA), the author conducts a multivariate linear regression model analysis using the SPSS software tool version 25.0 Research Model: X = β0 + β1*Y1 + β2*Y2 + … + βn*Yn + ε Where: β0: Constant ε: Random error Y: Independent variable X: Dependent variable Access to research topics 4.1 Approach to the topic Previous studies on consumers' online buying behavior show that theoretical models such as rational action theory and appropriately planned behavior theory study customers' online shopping behavior in this study In particular, the most important model in building research facilities is the TAM technology acceptance model 16 Through these models, the author can overcome the limitations of the TRA model, promote the effectiveness of the TPB model in the case of customer shopping and based on the TAM technology acceptance model to build a research model in the project with the topic "Factors affecting online shopping behavior of consumers in Hanoi" In this research project, the author applies the technology acceptance model (TAM) in combination with the theoretical model of rational action (TRA) Previously, other studies only applied to a TAM or TRA model In addition, the author fully synthesizes independent variables: attitudes, subjective norms, useful perceptions, risk perceptions, social influences and intermediate variables of online shopping intent and variables that depend on online shopping behavior 4.2 Summary of research problem and model proposal In the research proposal with the topic "Factors affecting online shopping behavior of consumers in Hanoi", the authors have compiled research papers from 2016-2021 to build a research model In addition, the authors also rely on the underlying theories to build the basis of the topic such as the theory of consumer behavior, the theory of research models including: planned behavior theory, rational action theory, technology acceptance model theory From previous studies by Ha Ngoc Thang and Nguyen Thanh Do (2016), Nguyen Minh Tuan and Nguyen Van Anh Vu (2020), Ta Van Thanh and Dang Xuan Thanh (2021), Anum Tariq et al (2016), Kok Wai Tham et al ( 2019), Meher Neger and Burhan Uddin (2020) and TRA, TAM models, the authors propose a research model consisting of independent variables: attitude, subjective norm, useful perception, risk perception, social influence, an intermediate variable: online shopping intent and online shopping behavior dependent variable 4.3 Propose future research ideas In the future, research directions need to focus on a specific market and a specific product Thereby, it is possible to better apply theoretical models that have been proven by many scientists such as TPB, TRA, TAM models Specifically propose some ideas as follows: - Factors affecting the behavior of buying skin care products through online platforms of Hanoi consumers - Factors affecting online consumer behavior on Lazada e-commerce site of Generation Z consumers in Vietnam In addition, further research directions should have a more representative sample selection method, overcoming the limitations caused by the non-export sample selection of the studied studies Specifically propose the following ideas: - Factors affecting online shopping behavior of consumers aged 25-30 in Hanoi - Factors affecting the online buying behavior of students of the National Economics University 17 4.4 Implications for management practices or policies For executives, the study aims to provide more information about the factors that influence and how they affect consumers' online buying behavior today In addition, the research also helps managers identify which solutions are suitable and adjust from reality based on academic research to provide complete solutions for businesses For policymakers , it is possible to recognize consumer online shopping behavior and changing consumer trends Thereby, it is possible to develop policies to develop e-commerce activities in Vietnam in a complete way and in accordance with the current needs of society 18 References Ahmad, R & Buttle, F., 2001 Customer retention: a potentially potent marketing management strategy Journal of Strategic Marketing, 9(1), pp 29-45 Ajzen, I., 1991 The Theory of Planned Behavior Organizational behavior and human decision processes, 50(2), pp 179-211 Ajzen, I & Fishbein, M., 1980 Understanding Attitudes and Predicting Social Behavior Englewood Cliffs ed NJ: Prentice-Hall Cai, Y & Cude , B J., 2016 Online Shopping Handbook of Consumer Finance Research, pp 339-355 Cooke, R & French, D P., 2008 How well the theory of reasoned action and 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Specifically propose the following ideas: - Factors affecting online shopping behavior of consumers aged 25-30 in Hanoi - Factors affecting the online buying behavior of students of the National Economics... with the study "Factors affecting online shopping behavior of consumers in Pakistan" The study aimed to evaluate the factors affecting the online shopping behavior of Pakistani consumers The results