factors affecting the purchasing behavior on e commerce platforms of students at fpt can tho university

Along with the popularity ofonline shopping, consumers'''' online purchase intention has become a topic of interest to manyresearchers in recent years Insley & Nunan, 2014, this is shown Cu

RMC301-Research methods in Communication

Factors affecting the purchasing behavior on e-commerce platforms of

students at FPT Can Tho University

Table of Contents

1 Introduction 2

1.1 Background 2

1.3 Related research documents 3

1.4 Research objective 3

1.6 Literature review 4

1.6.1 Ecommerce 4

1.6.2 Online purchase intention 4

1.6.3 Online purchase behavior 4

1.6.4 Related theoretical models 4

1.7 Hypothesis 5

2 Research method and procedures 8

2.1 Data processing method 8

2.2 Sampling process 8

2.3 Method analysis 8

3 Data analysis and finding 8

3.1 Descriptive statistics 8

3.2 Cronbach’s alpha test 11

3.3 Linear regression analysis 12

4 Discussion 14

5.1 Conclusion 14 5.2 Management implications 14

6 References 15

1 Introduction

1.1 Background

Today, electronic commerce (e-commerce) has become a field that has an extremely important impact on the economic growth of countries The development of e-commerce not only helps facilitate business activities but also provides many new values and meets new needs of businesses and consumers Therefore, every country in the world is interested in developing e-commerce

According to the Ministry of Industry and Trade, e-commerce continues to be one of the bright spots in Vietnam's digital economic development, with an estimated revenue of 20.5 billion USD

in 2023 Previously, if in 2018, revenue The country's retail e-commerce only reached about 8 billion USD By 2019, it had surpassed the 10 billion USD mark (reaching 10.8 billion USD) and increased to 11.8 billion USD in 2020 By 2022 , this number increased by 20% compared to the previous year, reaching 16.4 billion USD, accounting for 7.5% of retail revenue of consumer goods and services nationwide; The number of consumers participating in online shopping is over 54.6 million people, the online shopping value of one person reaches nearly 270 USD/year From there, it can be affirmed that Vietnamese e-commerce has grown strongly for many years and is one of the pioneering fields of the digital economy, creating motivation for economic development and leading digital transformation in business

In fact, e-commerce sites have constantly been born and developed with 4 applications: Shopee, Lazada, Tiki, Tiktok Shop being the most popular and constantly competing with each other to rise to a higher position in the field of commerce e-commerce Along with the popularity of online shopping, consumers' online purchase intention has become a topic of interest to many researchers in recent years (Insley & Nunan, 2014), this is shown Currently, a large number of research works have been published in different fields such as information systems, marketing, management and psychology (Cheung et al., 2005; Gefen et al., 2003a; Pavlou, 2003) Results of previous studies also show that product characteristics influence customers' online shopping intentions (Korgaonkar et al., 2006; Soopramanien et al., 2007) However, the results of some studies are still inconsistent and further investigation is needed (Phau and Poon, 2000; Vijayasarathy, 2002) Although there are many studies researching the relationship between customer characteristics and their online shopping intentions, however, the results of these studies are still not consistent, and there are still opinions contradictory One of the reasons for the differences between the results of previous studies is due to cultural differences between countries (Chau et al., 2002; Ko et al., 2004; Park and Jun, 2003; Zhou et al., 2007) Therefore, Delafrooz et al (2010) said that online shopping still needs to be studied more closely in specific contexts in different countries (Delafrooz et al., 2010) On the other hand, the rapid development

al., 2011) Therefore, studying consumers' online shopping intentions in the specific conditions and circumstances of Vietnam is not only meaningful in practice but also makes a theoretical contribution to supplement and improve the quality of online shopping further the results of previous research works

Mr Tran Van Trong, General Secretary of the E-Commerce Association (VECOM), commented that Vietnam is in a period of business boom through e-commerce platforms as the number of new online consumers continues to increase in number , quality "They buy more with increased purchase value and more sophisticated online shopping skills," he assessed But people's buying habits are also gradually changing with the emergence of new shopping trends Therefore, we decided to choose the research topic "Factors affecting the shopping intention on e-commerce platforms of FPT Can Tho University students"

1.3 Related research documents

Author Kim Hong Quan (2019) researched the topic "Factors affecting customers' online shopping decisions in Vietnam" The study has clarified 8 factors that influence customers' online shopping decisions in Vietnam, including: usefulness, ease of use, reliability, price, and perceived risk involved online transactions, product-related risk awareness, customer experience, online word of mouth Thereby, service providers can refer to the research's recommendations to enhance the competitiveness of their services in satisfying consumer needs Author Phan Thanh Ha (2017) and his colleagues researched the topic of factors affecting purchasing decisions on the Shopee trading floor of students at Ho Chi Minh City University of Technology The factors included in the model are trust, price, convenience, efficiency, influence group, and risk But after the research results, there are only five factors that influence the decision to buy products through the e-commerce platform Shopee: price, convenience, efficiency, influence group, and risk

Mohammad Hossein and colleagues (2012) researched the topic "An Analysis of Factors Affecting on Online Shopping Behavior of Consumers" Factors included in the study by the author include: financial risk, product risk, website/application quality, shipping risk, impact of family and friends, return policy, after-sales service, technology and product adoption, consumer awareness and lack of facilities for online shopping After testing, the results showed that financial risk and transportation risk have a negative impact on online consumer attitudes The remaining factors all have a positive influence

1.4 Research objective

Overall goal:

- Determine the influence of factors on purchase intention on e-commerce platforms

- Suggest management implications for traders on e-commerce platforms

Detail goal:

- Evaluate the influence of the factors Trust, Subjective norm, Perceived usefulness and Perceived ease of use on the purchase intention on e-commerce platforms of FPT Can Tho University students

- Suggest implications for administrators so that managers of e-commerce platforms have

1.5 Research question

- What factors affect the purchasing intention on e-commerce platforms of FPT Can Tho University students?

- What is the solution to help increase shopping needs on e-commerce platforms of FPT Can Tho University students?

1.6 Literature review

1.6.1 Ecommerce

According to the World Trade Organization (WTO), adopted by the Minister of Geneva in 1998,

“E-commerce includes the production, advertising, sales and distribution of products that are bought, sold and paid for on the Internet, but delivered and received in a tangible way, both delivered products as well as digital information through the Internet E-commerce is the use of electronic media such as the Internet to exchange, buy and sell products or services (Nguyen Dinh Luan, 2015) E-commerce is the buying, selling, and commercial activities that take place

on the Internet, where a customer will visit the seller's website, order and make payment for the product, and finally, the goods are delivered to the seller consumers through delivery staff E-commerce is often viewed in terms of e-business It also includes the exchange of data that facilitates the financing and payment aspects of business transactions (Mesenbourg, 2000)

1.6.2 Online purchase intention

Alsamydai (2016) asserted that purchase intention is driven by viral advertisements related to conceptual products or services or anything else According to Solomon (2014), intention is a factor that represents an individual's ability to perform future behavior Therefore, Delafrooz et

al (2011) said that "online shopping intention is the consumer's ability to make purchases via the Internet" Online shopping intention will determine the customer's strength in online shopping behavior (Salisbury, Pearson and Miller, 2002) Pavlou (2003), when a customer intends to use online transactions to shop, it is called online purchase intention

1.6.3 Online purchase behavior

Online shopping is defined as consumer behavior in shopping through online stores or websites using online purchase transactions (Monsuwe et al.2004) Similarly, according to Haubl et al (2000) online shopping is a transaction made by a consumer through a computer interface in which the consumer's computer is connected to the internet and can interact with the retailer's digital stores retail Online shopping persuades customers to buy products by making them feel the benefits and enjoyment when they shop (Ha et al.2009)

1.6.4 Related theoretical models

Theory of Reasoned Action - TRA

The theory of reasoned action model posits that behavioral intentions lead to behavior and that intentions are determined by individual attitudes toward the behavior, along with the influence of subjective norms surrounding the performance of those behaviors ( Fishbein and Ajzen, 1975) Where attitude is a positive or negative attitude towards an action or behavior, which can be measured by beliefs (Hale, 2003) Subjective norms are an individual's perception, with that individual's important references, that the behavior should or should not be performed (Fishbein

& Ajzen, 1975) TRA has been used by a number of authors in empirical research on consumer behavior in the context of online shopping, such as Vijayasarathy (2002) who studied consumers' internet shopping intentions based on TRA and adding product characteristic factors to the model Meanwhile, Yoh and colleagues (2003) used TRA in combination with innovation diffusion theory (IDT) to increase the explanatory power in their research model

Technology Acceptance Model – TAM

Figure 2 Technology Acceptance Model – TAM

The Technology Acceptance Model (TAM) is used to explain and predict technology adoption and usage behavior TAM is widely tested and accepted in information technology research and

is considered a model with good predictive value Accordingly, usage intention is significantly correlated with usage behavior, while other factors affect usage behavior indirectly through usage intention TAM points out that when users interact with new technology, key factors that can influence their decisions about using that technology include: perceived usefulness and perceived ease of use TAM has been widely used in information systems research and it has been successfully applied as a theoretical framework to predict online purchasing intentions and behavior (Chen and Tan, 2004; Hermández and et al 2010; Ho and Chen, 2013; Pavlou, 2003: Duong Thi Hai Phuong, 2012; Vijayasarathy, 2004) More specifically, authors have used TAM

to predict online purchase intentions and behavior for products such as books (Gefen et al., 2003a: Gefen et al 2003b: Lin, 2007), pants Austria (Ha and Stoel, 2009: Tong 2010 ) and financial services (Suh and Han, 2003)

1.7 Hypothesis

Based on previous research and the theoretical models mentioned above, we propose factors that influence purchasing intentions on e-commerce platforms of FPT Can Tho University students including: trust, subjective norms, perceived usefulness, perceived ease of use

Trust (TR)

According to Wu (2015), consumer trust in e-commerce websites affects online purchasing behavior despite the presence of risks Sri and colleagues (2013) believe that trust in online

addition, trust also has a positive influence on customer satisfaction Ngo Quoc Chien & Nguyen Thi Que Thanh (2017) proved that consumer trust affects customer satisfaction when shopping online On the other hand, lack of trust has been noted as one of the main reasons preventing consumers from participating in e-commerce (Jarvenpaa et al., 2000; y Monsuwé et al., 2004) Therefore, the proposed research hypothesis is:

H1: Trust has a positive impact on purchase intention on e-commerce platforms

Subjective norm (SN)

Research by Barkhi et al (2008) shows that subjective norms not only have an impact on customers' shopping intentions but also have a significant impact on consumers' attitudes toward online shopping Opinions of close people such as family, friends and colleagues, celebrities can directly or indirectly affect the trust of consumers and online suppliers through personal information directly or through the mass media Previous studies suggest that there is a positive relationship between subjective norms and intentions (Barkhi et al., 2008; Bhattacherjee, 2000; Hansen et al., 2004; Vijayasarathy, 2004; Yoh et al., 2003 ) Therefore, hypothesis H2 is proposed:

H2: Subjective norms have a positive impact on purchase intention on e-commerce platforms

Perceived usefulness (PU)

What is truly useful is the degree to which customers themselves believe that using a particular system will improve their purchasing efficiency (Davis, 1985) Unlike traditional services, online services are noticed by consumers because of their unique characteristics of being useful to consumers At the same time, Jarvenpaa et al (1997) conducted a study in the United States showing that convenience is a frequent cause of consumer participation in online services Therefore, when consumers feel the usefulness of new technological services, their intention to use is greater

H3: Perceived usefulness has a positive impact on purchase intention on e-commerce platforms

Perceived ease of use (PE)

Ease of use attributes are the level at which a person believes that using a particular system will require no effort (Davis, 1985) Hence awareness Usage greatly affects consumers' intention to use new technology computer services, when a computer user believes in the ability to perform a task (purchase) on a computer The ease of use depends on the design of the computer interface, the training program on how to use the computer, the language used, and the software installed

on the computer

H4: Perceived ease of use has a positive impact on purchase intention on e-commerce platforms

From the above four hypotheses, the model we propose is as follows:

Figure 3 Model of factors influencing purchase intention on e-commerce platforms

Trust (TR)

TR1 I believe that the e-commerce platform will work in

(2007), Hoang Quoc Cuong (2010)

TR2 I believe that the e-commerce platform will fulfill

their commitments

TR3 I am willing to provide information to register

accounts on e-commerce platforms

Subjective

norm (SN)

SN1 Friends and colleagues introduced me to using

e-commerce platforms for shopping

Bhattacherjee, (2000) SN2 Friends and colleagues encouraged me to use

e-commerce platforms to make purchases

SN3 Friends and colleagues often give positive reviewsabout e-commerce platforms

Perceived

usefulness

(PU)

Davis, Bagozzi & Warshaw (1989) PU2 I can search for all the items I need

PU3 I can shop without leaving home

Perceived

ease of use

(PE)

PE1 The interface of the sales website is easy to operate

Venkatesh & Davis (2001)

PE2 I easily make payments when making purchases

PE3 I can easily find information and products on

e-commerce platforms

PE4 I can easily process orders on e-commerce

platforms

Purchasing

intention

(PI)

PI1 I plan to use/continue to use the e-commerce

platform to make purchases

Bagozzi, Baumgatnr & Yi (1998)

for shopping

PI3 I am willing to recommend to my friends to shopon the e-commerce platform

Table 1 Scale of factors affecting purchasing intention on E-commerce platforms

2 Research method and procedures

2.1 Data processing method

Primary data was collected from March 9, 2024 to March 12, 2024

Secondary data was collected from relevent report

2.2 Sampling process

The sample size depends on the expectation of reliability, the data analysis method, the estimation method used, and the number of parameters to be estimated in the study According to Tabachnick and Fidell (2006), to conduct regression analysis, the minimum sample size is N > 8m + 50 (in which, m is the number of independent variables in the model) In this survey there are 4 independent variables, so the minimum number of samples needed to collect is 82 samples The results were 115 samples, in accordance with the requirements

2.3 Method analysis

After collecting and eliminating unsatisfactory questionnaires, the author coded and entered the data, then the data was processed using SPSS software The study's data were analyzed through the following steps:

- Descriptive statistics: helps the researcher understand the characteristics of the survey sample and also to consider possible relationships between variables

- Scale reliability testing: The purpose of this test is to find out whether the observed variables measure the same concept or not The value of more or less contribution is reflected through the total correlation coefficient (Corrected Item - Total Correlation) Thereby, allowing inappropriate variables to be eliminated in the research model According to Hoang Trong and Chu Nguyen Mong Ngoc (2008), Cronbach's Alpha coefficient from 0.8 to nearly 1 is a good measurement scale, from 0.7 to 0.8 is usable Cronbach's Alpha coefficient of 0.6 or higher can also be considered for use in new research contexts A usable scale must have a Corregated Item – Total Correlation coefficient of 0.3 or higher (Hair et al., 2010)

- Multiple linear regression: The regression method used in the thesis is the OLS least squares method The adjusted R2 coefficient is used to determine the suitability of the model, the F test is used to confirm the scalability of the model, the t test is used to reject the hypothesis of the regression coefficients of the population by 0

3 Data analysis and finding

3.1 Descriptive statistics

Frequencies statistic

Frequencies

Goods

Responses

Percent of Cases

a Group

Table2 Summary table of demographic frequency statistics

The survey results showed that there was no big difference between men (36.5%) and women (45.2%) in observed variables and most were final-year students (36.5%) When asked about

SchoolYear

Money

The average monthly spending ranges from 1 million VND to 3 million VND, accounting for the highest percentage (40%), then below 1 million VND (34.8%) and finally over 3 million VND (25.2%) ) For the multiple-choice question about items often purchased on e-commerce platforms, respondents chose fashion as the most frequently purchased item, followed by cosmetics, then electronic devices and houseware with the same ratio Equally, few respondents choose to buy food on e-commerce platforms and other items It is possible to comment and explain the characteristics of the respondents from the perspective of them being a student, that both men and women tend to buy goods on e-commerce platforms with high purchasing frequency and spending numbers There are two items with the highest purchase rate: fashion and cosmetics, which represent the personality characteristics and interests of today's young generation

Desccriptive statistic

Descriptive Statistics

Deviation

TR1 I believe that the e-commerce platform will work

TR2 I believe that the e-commerce platform will fulfill

TR3 I am willing to provide information to register

SN1 Friends and colleagues introduced me to using

SN2 Friends and colleagues encouraged me to use

e-commerce platforms to make purchases 115 3.89 1.041

SN3 Friends and colleagues often give positive reviews

PE1 The interface of the sales website is easy to

PE2 I easily make payments when making purchases 115 4.22 886

PE3 I can easily find information and products on e- 115 4.24 904