Nghiên cứu yếu tố ảnh hưởng tới ý định mua hàng trực tuyến của người Việt Nam: Mở rộng lí thuyết mô hình chấp nhận công nghệ (TAM)

Chia sẻ: _ _ | Ngày: | Loại File: PDF | Số trang:16

Thêm vào BST

Báo xấu

13
lượt xem 4
download

Download Vui lòng tải xuống để xem tài liệu đầy đủ

Nghiên cứu khảo sát các yếu tố khác nhau ảnh hưởng đến ý định mua sắm trực tuyến của người tiêu dùng Việt Nam. Mô hình chấp nhận công nghệ (TAM) được sử dụng làm lí thuyết nền tảng để phát triển khung khái niệm nhằm kiểm tra ảnh hưởng của các yếu tố đến ý định của người tiêu dùng đối với mua sắm trực tuyến.

Chủ đề:

Bình luận(0) Đăng nhập để gửi bình luận!

Lưu

Nội dung Text: Nghiên cứu yếu tố ảnh hưởng tới ý định mua hàng trực tuyến của người Việt Nam: Mở rộng lí thuyết mô hình chấp nhận công nghệ (TAM)

NGHIÊN CỨU YẾU TỐ ẢNH HƯỞNG TỚI Ý ĐỊNH MUA HÀNG TRỰC TUYẾN CỦA NGƯỜI VIỆT NAM: MỞ RỘNG LÍ THUYẾT MÔ HÌNH CHẤP NHẬN CÔNG NGHỆ (TAM) Lê Thị Nương1* 1 Trường Đại học Hồng Đức * Email: lethinuongkt@hdu.edu.vn Ngày nhận bài: 26/09/2023 Ngày nhận bài sửa sau phản biện: 24/11/2023 Ngày chấp nhận đăng: 15/12/2023 TÓM TẮT Nghiên cứu khảo sát các yếu tố khác nhau ảnh hưởng đến ý định mua sắm trực tuyến của người tiêu dùng Việt Nam. Mô hình chấp nhận công nghệ (TAM) được sử dụng làm lí thuyết nền tảng để phát triển khung khái niệm nhằm kiểm tra ảnh hưởng của các yếu tố đến ý định của người tiêu dùng đối với mua sắm trực tuyến. Nghiên cứu sử dụng bảng câu hỏi có cấu trúc để thăm dò ý kiến của 468 người tiêu dùng về các yếu tố ảnh hưởng đến hành vi mua sắm trực tuyến và dữ liệu thu được phân tích bằng phần mềm SPSS 20.0. Kết quả nghiên cứu cho thấy ảnh hưởng xã hội có tác động mạnh nhất đến ý định mua hàng trực tuyến, tiếp theo là trải nghiệm và cảm nhận tính hữu ích, niềm tin cảm nhận có tác động không đáng kể đến ý định mua hàng trực tuyến, trong khi rủi ro cảm nhận có tác động tiêu cực đến ý định mua hàng trực tuyến. Kết quả nghiên cứu là tài liệu quý giá để các doanh nghiệp trực tuyến xây dựng chiến lược kinh doanh phù hợp nhằm thu hút nhiều khách hàng hơn. Từ khóa: kinh doanh trực tuyến, mô hình chấp nhận công nghệ (TAM), ý định mua hàng trực tuyến. FACTORS INFLUENCING ONLINE PURCHASE INTENTION AMONG VIETNAMESE: EXPANSION OF TECHNOLOGY ACCEPTANCE MODEL (TAM) THEORY ABSTRACT The study investigated various factors influencing Vietnamese consumers' intentions towards online shopping. The Technology Acceptance Model (TAM) was used as a foundational theory to develop a conceptual framework to examine the influence of diverse factors on consumer intentions toward online shopping. The study used a structured questionnaire to poll the opinions of 468 consumers on factors affecting online shopping behavior, and the data obtained was analyzed using SPSS 20.0 software. Research results show that social influence has the most potent effect on online purchase intention, followed by experience and perceived usefulness; perceived trust has an insignificant impact on online purchase intention, while perceived risk has a negative impact on online purchase intention. The research results are valuable literature for online businesses to develop appropriate business strategies to attract more customers. Keywords: online business, online purchase intention, Technology Acceptance Model (TAM). Số 11 (2023): 29 – 44 29
1. INTRODUCTION in the relationship between social commerce The emergence of smartphones, mobile constructs, perceived ease of use, perceived communication devices, and other wireless usefulness, and intention to purchase. transmission technologies has made it In recent years, the technology acceptance possible for consumers to make purchases model (TAM) has been used by many anytime, anywhere, and in various methods. researchers to understand consumer shopping Online shopping has become a trend in recent behavior. TAM is a theory that explains the years due to the development of technology factors influencing awareness and intention to and the superior values that online shopping use technology. It is a model that predicts brings compared to traditional shopping customer attitudes and loyalty toward the (Yoke Cheng et al., 2022). The benefits of benefits and uses of information (Davis, 1989). online shopping include saving time and The current study examines the relationship effort by diversifying choices so customers between factors in the TAM theoretical model can easily make the most optimal shopping and consumers' online shopping behavior. decisions in terms of quality and price, However, it adds several other factors, such as payment and delivery methods, and after- perceived trust, risk, experience, and social sales service. However, online shopping also influence. There have been many studies has limitations, such as consumers quickly applying the TAM theoretical model to losing balance in shopping, sometimes evaluate factors affecting consumers' online buying according to preferences and habits purchasing behavior (Heijden et al., 2003; but not having real needs, leading to waste. Hatamifar et al., 2021; Gunawan et al., 2023). However, research is limited to the theoretically In addition, shopping in a virtual proposed group of factors, including perceived environment also concerns customers about usefulness and ease of use. It has been proven quality and delivery methods, which directly that there are many other factors related to affects online shopping intention (Aziz & technology that have a significant impact on Wahid, 2018). Although the trend of online online purchasing behavior; therefore, shopping is increasing, there are still many expanding the TAM theoretical model in customers who need clarification and support researching people's online purchasing to buy online due to a lack of trust. Therefore, behavior is needed. The results of the current research on online purchasing behavior in research will be the foundation for helping today's time is vital. Many researchers have administrators in Vietnam's e-commerce sector also delved into the factors that promote come up with appropriate strategies to promote consumers' online purchasing behavior. consumers' online purchasing behavior. Specifically, Yoke Cheng et al. (2022), 2. METHODOLOGY Hatamifar et al. (2021), and Binh et al. To evaluate the influence of factors on the (2022) examined the increase in consumer online purchase intention of Vietnamese intentions toward online shopping. They people, six main factors are considered: emphasized that there are many factors Perceived usefulness, perceived ease of use, affecting consumers' online purchasing perceived risk, perceived trust, experience, behavior in different contexts and and social influence. The questionnaire was environments. Specifically, the study of sent directly and via email to consumers in Yoke Cheng et al. (2022) showed that Vietnam in the period from March to May perceived trust has a significant influence, 2023. 500 samples of questionnaires were while perceived ease of use and perceived sent, and 468 valid questionnaires were risk have an insignificant influence on collected for analysis. Random sampling is people's online purchase intention. Shekhar used to select respondents. Data were & Jaidev (2020) found that trust in social collected using a 5-point Likert scale ranging commerce has been identified as a mediator from strongly dissatisfied to strongly satisfied. 30 Số 11 (2023): 29 – 44
KHOA HỌC XÃ HỘI Table 1. Variables of the study Factors Variables Sources Buying online saves time Buying online helps save on travel costs. Hatamifar et al. Perceived (2021), Binh et al. usefulness Customers have many choices when shopping online. (2022), Yoke Cheng There are many attractive promotions only available for online et al. (2022) purchases. Using a smartphone to shop online requires little effort. Online shopping applications are straightforward to use. Hatamifar et al. Perceived ease (2021), Binh et al. of use Online shopping applications are easy to understand and (2022), Yoke Cheng straightforward. et al. (2022) The steps to order online are very simple. Buying online can put product quality at risk. Buying online can put personal information at risk. Yoke Cheng et al. Perceived risk (2022). Buying online can be financially risky. Buying online may run the risk of delivery problems. Online shopping through mobile apps is reliable in Vietnam. Online shopping through mobile apps is trustworthy in Hatamifar et al. Vietnam. (2021), Binh et al. Perceived trust (2022), Yoke Cheng Online retailers provide reliable information and always keep et al. (2022) their promises. In my future shopping, I will use mobile apps and trust them. I bought products frequently through mobile apps. Mobile apps offer more than traditional shopping methods; hence, I get more experiences and fun. Hatamifar et al. Experience I am knowledgeable about using mobile apps before I (2021) purchase anything. Experience is an essential factor that helps me make an online purchasing decision. Family, friends, and acquaintances introduced and encouraged me to shop online. Before participating in online shopping, I read a lot of information and reviews on e-commerce sites, forums, and Social influence social networks. Gunawan et al. (2023) Information in the mass media influences my online shopping intention. Sellers' feedback and other customers' comments on e- commerce sites influence my online shopping decision. I intend to engage in online shopping soon. Hatamifar et al. Online purchase I will introduce family and friends and post information about (2021), Binh et al. intention participating in online shopping on my social media accounts. (2022) I will use online shopping instead of traditional shopping. Số 11 (2023): 29 – 44 31
The questionnaire is divided into two main perceived trust, perceived risk, experience, and parts. The first part includes respondents' social influence. information, and the second part looks at the 3.1.2. Online Purchase Intention critical variables of this study such as perceived perceptions, perceived ease of use, According to Lodesso et al. (2019), perceived risk, perceived trust, experience, intention is a factor that represents an social influence, and online purchase individual's ability to perform future intention. The questionnaire is adapted from behavior. Behavioral intention precedes previous studies combined with interviews actual behavior and is also a factor in and in-depth consultation with some experts predicting whether the behavior will be in online shopping in Vietnam. This study performed (Ajzen & Fishbein, 1980). In applies multiple regression methods through other words, user behavior is influenced by SPSS to analyze data (Table 1). behavioral intentions (Davis, 1989). According to Ajzen (1991), intention is 3. RESEARCH CONTENT assumed to include motivational factors that 3.1. Literature review and hypotheses influence behavior, which are signs showing development willingness and effort to perform the behavior. According to the theory of planned 3.1.1. The theory of Technology Acceptance behavior (TPB), the intention to perform a Model (TAM) behavior is influenced by attitudes toward the The Technology Acceptance Model behavior, subjective norms, and perceived (TAM) is a theoretical model of technology behavioral control (Ajzen, 1991). The usage behavior introduced by Davis (1989). stronger the intention for a behavior, the This model explains how users evaluate and higher the likelihood that the behavior will be use new technology. According to TAM, performed (Ajzen, 1991). Online purchase users' technology usage behavior depends on intention is a customer's intention to use two main factors: Perceived usefulness and online channels such as websites and social Perceived ease of use. Perceived usefulness is networks to purchase goods and services. In the degree to which users believe the e-commerce, online purchase intention is technology will benefit their work or needs. when a customer wants to make a transaction Perceived ease of use is the degree to which through a website to own goods and services the user believes using the technology will be to satisfy their needs. According to Zhang et easy and uncomplicated. According to TAM, al. (2020), online shopping intention is if users believe that technology will bring consumers' willingness to purchase products value to their work or needs and that using it is and services after they review related online easy, they will use it (Hatamifar et al., 2021). comments. Shi Wen et al. (2020) affirmed that online shopping intention is inevitable Due to appreciating the TAM model as a when consumers know the role of online solid theoretical foundation for evaluating shopping. After the Covid-19 pandemic, technology use behavior, many scholars have consumer awareness of online shopping used TAM to analyze technology application behavior has increased quickly. They shop behavior in many different cases (Hubert et al., online not only for convenience and cost 2017). However, TAM is often a technology- savings but also because of safety concerns. based model whose underlying structures do not comprehensively promote diversity in 3.1.3. Proposed research model users' task environments; therefore, it needs to According to Ajzen (1991), intention is be expanded to explain better innovative directly influenced by attitudes, subjective technology adoption behavior (Schepers & norms, and perceived behavioral control. Wetzels, 2007). This study enhances the TAM Factors that motivate consumers to model by adding four additional constructs: participate in online shopping come from 32 Số 11 (2023): 29 – 44
KHOA HỌC XÃ HỘI convenience, variety of products and shopping and different research purposes, services, rich information, easy access, and factors affecting consumers' online shopping ease of shopping. According to Davis (1989), intentions will be identified and selected. online shopping intention is influenced by Therefore, the determination of factors is quite perceived usefulness and ease of use. Al flexible, depending on the unique advantages Hamli & Sobaih (2023) show that product of each different market segment. variety, payment methods, and psychological Based on the above theory, along with factors are three critical factors affecting related research works, this study examines online shopping behavior, while convenience customers' online purchasing intentions and trust factors do not have a significant based on the TAM framework. However, impact on consumers' online shopping according to (Al-Hattami et al., 2023), the decisions in the context of COVID-19. In original TAM constructs may need to online shopping, consumers often face risks appropriately capture the essential beliefs such as financial risks, information security influencing consumers' online purchasing risks, product risks, risks of not receiving behavior. Therefore, in the context of this goods, and return policy risks (Tham, et al. study, other essential factors need to be 2019). Ventre & Kolbe (2020) found that considered to understand consumers' perceived usefulness influences trust and engagement intentions better when making online purchase intention, trust has an inverse online purchases. The current study extends relationship with perceived risk and TAM by incorporating external factors such influences positively in online purchase as perceived trust, perceived risk, experience, intention, while perceived risk has no and social influence to evaluate Vietnamese relationship with online purchase intention. people's online shopping intentions. The In a specific context, depending on proposed research model is as follows consumers' awareness and perception of online (Figure 1). Figure 1. Conceptual framework 3.1.4. Hypotheses development shown that the experience of convenience when using technology has a direct impact on This study examines customers' intention post-purchase behavior customers and to purchase online based on the TAM purchase intention through future technology framework. Perceived benefits are one of the applications. key drivers of technology adoption on the platform. Convenience is an advantage of Although research on TAM provides new technology that makes it easier for insights into technology use, it focuses on customers to purchase through applications perceived ease of use and perceived (Davis, 1989). Although it is commonly usefulness as determinants of use or intention believed that ease of use is not as important to use. It ignores other external factors that as perceived benefits, it has been consistently may act as determinants of (Igbaria & Iivari, Số 11 (2023): 29 – 44 33
1995). Perceived ease of use and perceived (2011) suggested that perceived usefulness usefulness are relevant factors determining does not have a significant influence on technology acceptance, TAM must be Internet purchasing behavior in Iran. It may expanded by involving other factors (Xu et be due to the different views of respondents al., 2021). Initial TAM constructs may not from developed and developing countries appropriately capture essential beliefs regarding the perceived beneficial influence influencing consumers' online purchasing on their internet shopping behavior. behavior (Al-Hattami et al., 2023). Concerns about price, quality, durability, and Therefore, in the context of this study, other product-related aspects are critical other essential factors need to be considered drivers of purchasing decisions in developed to understand consumers' engagement countries, but considerations may be intentions better when making online different in developing countries. purchases. The current study extends TAM Therefore, the study proposes the by incorporating external factors such as following hypothesis: perceived trust, perceived risk, experience, and social influence to evaluate Vietnamese H1: Perceived usefulness has a positive people's online purchase intentions. influence on online purchase intention. Perceived usefulness (PU) Perceives ease of use (PEOU) According to Davis (1989), perceived Perceived Ease of Use is the level at usefulness is the degree to which an which a person believes using a particular individual believes using a particular system system will be effortless (Davis,1989). In will increase job performance. Perceived online shopping, PEOU can be defined as the usefulness, including convenience, financial, degree to which consumers believe that they time, and energy savings, are reasons that do not need to make an effort when shopping promote online shopping intention. The online (Shekhar & Jaidev, 2020). Similar to perceived usefulness of a website often PU, the role of PEOU has been shown to depends on the effectiveness of technological have a significant influence on online features such as advanced search engines and shopping intention through attitude. personalized services that a business According to Yoke Cheng et al. (2022), provides to consumers. Many studies have perceived ease of use is the belief that shown a positive correlation between consumers have that using technology to usefulness and consumer behavior (Juyal, make online purchases is easy, less time- 2018; Xu et al., 2020; Ha et al. 2021); consuming, and makes an effort to learn how suppose consumers realize that buying online to use it. Therefore, perceived ease of use requires little effort. In that case, impulse dramatically affects consumers' intention to purchases are more likely because it is use new technological services when a phone known that purchases involve investments of or computer user believes in the ability to time, money, and mobility (Al-Hattami et al., perform a task (purchase) on their phone or 2023). Most studies have shown convenience computer quickly, depending on the many and time savings as the main reasons interface designs of these electronic devices. consumers shop online. Research has shown Research has shown that ease of use is that searching for products and services via strongly correlated with the ease of the Internet, particularly e-commerce sites, participation in online shopping systems (i.e., will be quick and convenient and reduce websites, stores, apps) (Binh et al., 2022). effort and costs. Hernández et al. (2011) Perceived ease of use motivates customers in revealed that perceived usefulness has a online shopping. In the Vietnamese market, significant influence on online shopping Thang & Lien (2017) and Binh et al. (2022) behavior in Spain. However, Aghdaie et al. confirm that perceived ease of use has a 34 Số 11 (2023): 29 – 44
KHOA HỌC XÃ HỘI positive impact on online shopping intention. Perceived Trust (PT) On that basis, the study proposes the Trust is the expectation that individuals or following hypothesis: companies, through interactions, will behave H2: Perceived ease of use positively ethically, reliably, and by social norms. impacts online purchase intention. Perceived trust refers to an assumption about Perceived Risk (PR) current human behavior in society. Puspitarini et al. (2021) added that perceived Perceived risk is a customer's perception trust is an established psychological state that of the possibility of gain and loss in online indicates a consumer's willingness or transaction outcomes (Tham, et al. 2019). acceptance of vulnerability to positive Perceived risk refers to a consumer's expectations that individuals will behave in a perception of uncertainty and adverse certain way. Trust creates a positive image in consequences when participating in a customers' minds about a product/service and particular activity. Risks when buying online companies doing business in e-commerce. can include Product risks, financial risks, and Trust is a factor that significantly influences information security risks (Yoke Cheng et consumers' intentions and behavior in both al., 2022). These risks occur mainly because online and traditional shopping. When the buyer does not see the actual image of the customers put trust in their online shopping product and does not come into direct contact activities, they evaluate that activity well, with the salesperson, which causes meaning they have a positive attitude and uncertainty in the consumer's mind about the vice versa. According to Puspitarini et al. expected performance of the product. (2021), customers often rely on their trust in Furthermore, all transactions are done a product or service to make purchasing through the website, not directly as in decisions. Sallam (2016) affirms that trust is traditional transactions. In traditional the most critical long-term barrier to retaining a customer and making them commerce, customers can go directly to the repurchase a product or use a service again. store, touch, feel, or even try the product In addition, trust can also lead to consumers' before purchasing, while online consumers willingness to engage in positive behaviors. cannot have such conditions. In a virtual world entirely of ambiguity, Ventre & Kolbe (2020) argues that online shopping is always ambiguous, and perceived risk is a decisive factor in there is always uncertainty due to consumers' explaining consumer buying behavior inability to physically evaluate products because consumers are more concerned with before purchasing. Therefore, consumers avoiding loss or damage to themselves than tend to trust information sources on websites. trying to achieve successful transactions. However, inconsistent information has made Consumers' perceived risk has been shown to consumers hesitant to shop online (Rita et al., influence their online decisions (Simon Kofi 2019). Trust influences consumers' online Dogbe et al., 2019). Most empirical studies shopping intention toward a retailer's web show that the perceived risk has a negative source (Yoke Cheng et al., 2022). Therefore, impact on online purchase intention (Tham, the study proposes the following hypothesis: et al. 2019). When consumers accept risks because they trust a sales website, they are H4: Perceived trust has a positive impact likelier to lose trust when encountering on online purchase intention. problems. On that basis, the study proposes Experience (EP) the following hypothesis: Previous online purchase experience can H3: Perceived risk has a negative impact be understood as a consumer's intention to on online purchase intention. repurchase a product or service on an online Số 11 (2023): 29 – 44 35
platform influenced by a history of previous influenced by others (Mei & Boon Aun, Internet purchasing behavior (Monsuwe´ et 2019). A person's online purchasing beliefs al., 2004). Weisberg et al. (2011) found that and behavior can be influenced by word-of- purchase experiences are essential for mouth information from relatives, friends, or predicting customers' future purchase even information spread on social networking intentions, and online experiences are also sites from strangers (Brusch & Rappel, 2020). closely related to the benefits of online Many of an individual's decisions about shopping and consumers' perceived risk whether or not to use an online shopping factors. Previous studies show that a service are greatly influenced by the beliefs, successful online shopping experience attitudes, behaviors, or opinions of others through an app improves repurchase intention regarding the use, purchase, and delivery of (Maruping et al., 2016). Research also shows electronic applications. Sometimes, a that people who have had negative person's decision to buy online or not is just experiences when shopping online are not because other people do the same, or a close motivated to shop online again, at least for a group's perception of online shopping specific period (Stouthuysen et al., 2018; behavior (positive or negative) also affects an Juyal, 2018). Previous online shopping individual's online purchasing decision. The experiences can help customers minimize opinions of close people (such as family, risks. There are more risks when customers friends and colleagues, celebrities...) can buy products on social networks than on a directly or indirectly influence consumers' standard e-commerce website. Therefore, the trust in online vendors. Dewi et al. (2020) and confidence and skills online shoppers gain Gunawan et al. (2023) concluded that social from their online shopping experience can influence positively impacts a person's online help buyers overcome risks and build trust. purchase intention. In the context of the Previous experience will strengthen the present study, it can also be proposed that: customer's trust and confidence in that online shopping platform, especially when the H6. Social influence positively impacts retailer's website meets customer expectations online purchase intention. and satisfaction (Pappas et al., 2012). 3.2. Results and data analysis Therefore, the study proposes the 3.2.1. Descriptive analysis following hypothesis: a. Characteristics of the research sample H5: Experience has a positive impact on The survey results of 468 customers online purchase intention. showed that 283 participants were female Social influence (SI) (accounting for 60.47%). In reality, customers Social influence is a decisive factor in participating in online shopping are women in behavioral intention, such as subjective norm Vietnam. In terms of age, the number of people according to TRA theory (Ajzen, 1991) or between the ages of 30 and 50 participating in TAM (Davis, 1989). In online shopping, the survey was the most (50.21%), followed by social influence is even more critical due to those aged 18 to 30 (accounting for 31.2%). the cultural and specific characteristics. These people have stable incomes and often Social influence refers to the impact of social buy things for themselves and their families. factors (usually surrounding people, Most survey respondents are officials, civil servants, and office workers (accounting for concepts, and ethics) on the behavior of an 48.08%), followed by business people individual or organization. Studies show that (accounting for 21.79%) (Table 2). social influence has a significant impact on consumer behavior because no one in this Regarding personal income, the income world can live a life without ever being level accounts for the highest percentage 36 Số 11 (2023): 29 – 44
KHOA HỌC XÃ HỘI from 5 to less than 10 million (accounting for all variables ranges from 3.429 to 4.00 with a 39.32%), followed by 10 to 20 million standard deviation from 0.58858 to 0.90185, (accounting for 38.25%). Regarding the indicating that most of the respondents in this frequency of online purchasing, most study were answered on a scale from normal respondents have been purchasing online to agree. People have a good assessment of sometimes and occasionally; however, the factors affecting online purchase 11.54% have never purchased online. This is intention, and people's online purchase the market for online businesses to look intention is also rated at a high level. This forward to in the future (Table 2). shows that online shopping is gradually becoming a current and future shopping b. Descriptive analysis for mean behavior trend. However, to measure the This part of the analysis was performed to uncertainty, the standard deviation is used. A check the customer's level of agreement with high standard deviation indicates more each variable. A mean value of less than 3 variation in the data and that the values are far indicates low impact, less than 4 indicates from the actual value. Therefore, in this moderate impact, and a value of 4 or greater study, the S.D. values are shallow, indicating than 4 indicates high impact. that the values are close to the actual values Table 3 indicates that the mean range of and the respondents' responses differ. Table 2. Respondents’ information Indicators Frequency Percentage (%) Male 185 39.53 Gender Female 283 60.47 Under 18 4 0.85 From 18 to 30 146 31.2 Age From 30 to 50 235 50.21 Over 50 84 17.95 Pupil, Student 49 10.47 Officials, civil servants, 225 48.08 office workers Occupation Businessman 102 21.79 Workers 76 16.24 Others 16 3.42 Less than five 58 12.39 mills.VND From 5 to less than 10 Monthly Personal Mills.VND 184 39.32 Income From 10 to less than 20 179 38.25 Mills.VND From 20 mills.VND 47 10.04 Quite often 36 7.69 Usually 69 14.74 Frequency of online Sometimes 184 39.32 purchasing Occasionally 125 26.71 Never 54 11.54 Số 11 (2023): 29 – 44 37
Table 3. Mean Analysis instrumentation is most relevant, and the results are accurate and reliable. Variables Mean Std.Deviation N 3.2.3. Multiple regression analysis Perceived 3.9663 .58858 468 usefulness (PU) Multivariate analysis examines the extent Perceived ease of the relationship between two or more 3.9343 .62156 468 variables. Furthermore, it shows the effect of of use (PEOU) the independent variables on the dependent Perceived Risk 3.4290 .90185 468 variable. This test is interpreted according to (PR) the value of β; if it is significant at a Perceived Trust significance level less than 0.05, we will 3.9631 .66304 468 (PT) accept the hypothesis; otherwise, we will Experience (EP) 3.8937 .62838 468 reject it. In particular, it is a statistical tool that checks how many independent variables Social influence 3.8782 .61291 468 are related to one dependent variable. (SI) However, the model summary and coefficient Online Purchase table are presented below. 4.0000 .64968 468 Intention (OPI) Table 5 shows that the model's adjusted R² 3.2.2. Reliability analysis is 0.520 with R² = 0.526, showing that the linear regression explains 52 % of the The reliability of the data collection tool is variance in the data. The R-squared value is critical for the completeness and accuracy of the proportion of variance in the dependent the analysis. Indeed, it is impossible to ignore variable explained by the independent providing evidence about the data for data variables. Therefore, the R-squared value of analysis. Therefore, it is essential to check the 0.520 shows that independent variables reliability before further analysis. For reliable (Perceived usefulness, perceived ease of use, data, Cronbach's Alpha value must be equal perceived risk, perceived trust, experience, to or greater than 0.70 (Hair et al., 2010). and social influence) explain the change and Table 4 shows that Cronbach's alpha predict the behavior of online purchase values for all variables are more significant intention. However, in the case of the current than 0.7 and less than 0.95, which shows that model summary results, the value of R = .725 all variables are reliable for the study, indicates a moderate degree of predictability. Table 4. Reliability Analysis Cronbach’s Alpha Variables Number of variables Value Perceived usefulness (PU) 4 0.814 Perceived ease of use (PEOU) 4 0.857 Perceived Risk (PR) 4 0.928 Perceived Trust (PT) 4 0.834 Experience (EP) 4 0.782 Social influence (SI) 4 0.774 Online Purchase Intention (OPI) 3 0.843 38 Số 11 (2023): 29 – 44
KHOA HỌC XÃ HỘI Table 5. Model Summary Std. Change Statistics Adjusted R Error of R Durbin- Model R R F Sig. F Watson Square the Square df1 df2 Square Estimate Change Change Change 1 .725a .526 .520 .45014 .526 85.299 6 461 .000 1.744 a. Predictors: (Constant), SI., PR, PEOU, EP., PT., PU b. Dependent Variable: OPI Table 6. Coefficientsa Unstandardized Standardized Collinearity Coefficients Coefficients Statistics Model t Sig. Std. B Beta Tolerance VIF Error (Constant) - .021 .249 -.085 .932 PU .332 .040 .301 8.384 .000 .800 1.250 PEOU .144 .036 .137 4.035 .000 .886 1.129 1 PR -.115 .024 -.160 -4.902 .000 .964 1.038 PT .079 .034 .080 2.339 .020 .876 1.142 EP .227 .035 .219 6.503 .000 .904 1.106 SI .346 .037 .326 9.409 .000 .854 1.171 a. Dependent Variable: OPI The above-denormalized coefficients intnetion. Social influence is the critical show that the online purchase intention factor that has the most significant influence changes with an independent variable on online purchase intention, followed by (Perceived usefulness, perceived ease of use, Perceived usefulness. At the same time, the perceived risk, perceived trust, experience, research results show that Perceived trust has and social influence) when all variables other a positive but insignificant effect on online independence remain unchanged. β is purchase intention, and Perceived risk has a significant if p < 0.05. Therefore, table 6 negative effect on online purchase intention. above shows the impact of the independent 3.3. Discusion variable on the dependent variable, the β value of Perceived usefulness (β = .301; Sig. The study developed an extended TAM = 000), perceived ease of use (β = .137; Sig. model by adding perceived risk, perceived = .000), perceived risk (β = -.160; Sig. = trust, experience, and social influence as .000), perceived trust (β = .080; Sig. = .020), independent variables affecting Vietnamese experience (β = .219; Sig. = .000), Social people's online shopping intention. Research influence (β = .326; Sig. = .000) shows the results show that 5 out of 6 factors proposed impact of these variables on online purchase in the model positively impact the online Số 11 (2023): 29 – 44 39
purchasing intentions of consumers in businesses need to have strategies to increase Vietnam. On the contrary, there is one factor the quality of products and services so that (Perceived Risk) that has a negative impact customers feel that purchasing online brings on consumers' online purchasing intention. them more value than traditional purchases, thereby promoting customers' online First, Social influence has the most purchasing behavior regularly. significant influence on consumers' purchasing intentions (β = 0.326; Sig. = Third, experience has the third largest 0.000). This is understandable because the positive impact on consumers' online survey subjects here are pretty diverse: some purchase intention. As stated in the literature have bought online many times, and some review, when customers have a good have never bought, so the opinions of around experience with online shopping, they will people are significant for people's purchasing tend to repeat this behavior the next time. behavior. This explains that when many Therefore, creating a positive customer people in society (brothers, friends, and experience the first time they purchase is others in the community) have positive essential for online businesses. This result is reviews about online shopping, more similar to the research results of Monsuwe´ et consumers tend to use online shopping al. (2004), and Weisberg et al. (2011). channels. This result is similar to the research Fourth, perceived ease of use positively results of Yang et al. (2012), Gunawan et al. impacts Vietnamese people's online purchase (2023) and Miranda et al. (2014) when intention. This result provides empirical proving that the opinions of friends and support for TAM and supports previous relatives positively impact consumer research by Yoke Cheng et al. (2022). Buying behavior toward online shopping. online means using technology to interact Vietnamese culture is a collective, where with the seller. Although the digital age has group opinions and desires often have a more made the application of technology in substantial impact on someone's behavior business and the daily activities of businesses than individual opinions and desires. and consumers popular, not everyone can use Therefore, in such an environment, the technology easily. Therefore, the simpler and influence of opinions from the community easier to use technology applications and society will significantly impact (specifically applications in online shopping) consumer behavior. Online retailers need to are, the more they will motivate customers to have a strategy to increase positive comments access and make online purchasing decisions and reviews about their products/services, (Venkatesh, 2000; Shekhar & Jaidev, 2020). focusing on creating positive social impacts Perceived trust has an insignificant and minimizing and controlling negative impact on Vietnamese people's online comments and reviews from customers. purchase intention. This may explain why, Next, Perceived usefulness has the for many Vietnamese people, the reputation second most significant impact on of e-commerce sites and online business consumers' online purchase intention (β = brands does not affect their purchasing 0.301; Sig. = 0.000). When customers realize behavior because they believe that that buying online brings them much value, purchasing behavior needs to be realistic, so what they receive is more significant than they rely on many factors closer to them (for what they have to spend, or online purchases example, the personal experiences of bring more value than traditional purchases, relatives) rather than trusting the reputation customers will tend to make online of e-commerce sites. purchases. The current research results are Finally, this study confirms the negative similar to the research results of Binh et al. impact of perceived risk on online purchase (2022) and Al-Hattami et al. (2023). Online intention. Furthermore, it strengthens the 40 Số 11 (2023): 29 – 44
KHOA HỌC XÃ HỘI literature by illustrating a more significant comprehensive view of consumers' online negative effect of perceived risk on online shopping behavior, thereby building better purchase intention (Ha et al., 2021). The business development policies for the findings of this study reflect the limitations of potential markets. TAM mentioned by Venkatesh (2000). The study only tested the factors of Consumers pay more attention to possible perceived usefulness, perceived ease of use, risks due to their greater purchasing power and higher ordering frequency, making them perceived trust, experience, social influence, more sensitive to risks. People are going and perceived risk on online purchase through the post-Covid-19 economic crisis, intention, while there are still many other so they always focus on financial security. factors that can affect online purchase Therefore, having a negative perception of intention, such as perceived behavioral online shopping may negatively affect control, convenience, price expectations, people's online purchase intention. seller size and reputation, legal influence... have not been mentioned in this study. This is 4. CONCLUSION also an issue that future studies can develop In general, online shopping is a common and perfect to increase the explanatory level trend for consumers today. This study applied of the model. Research conducted for the several theoretical perspectives to propose a entire Vietnamese population is too broad. research model on factors affecting the online Further research should be conducted for purchasing behavior of Vietnamese people. each customer group to gain a deep The author took TAM as the original model understanding of the psychology and and expanded some factors such as perceived purchasing behavior of each target group. trust, perceived risk, experience, and social There should be a comparison of the influence to ensure the model can explain the differences in the online shopping behavior online purchasing behavior of customers in of target groups according to demographic Vietnam. The author has built and adjusted a differences such as age, gender, education research model to suit the context and level, and personal income to find appropriate research object, including seven factors with solutions to promote online purchasing 24 observed variables affecting online behavior for each target group. This research shopping intention, including six only studies the online purchasing intentions independent factors (variables) are perceived of individual customers, not mentioning the usefulness, perceived ease of use, perceived intentions of organizational customers. trust, experiences, social influence, and Therefore, research on the relationship perceived risk. After data was collected from the questionnaire, it was cleaned and between factors affecting online purchasing analyzed using SPSS 20.0 software. Research intentions of organizational customers is also results indicate that social influence on a direction for further development. perceived usefulness, experience, and ease of REFERENCES use positively and significantly influences online purchase intention. In contrast, Aghdaie, S., F., A., Fathi, S., & Piraman, A. perceived trust has no influence and (2011). An analysis of factors affecting perceived risk negatively affects the online the consumer’s attitude oftrust and their purchasing intention of Vietnamese people. impact on internet purchasing behavior’. International Journal Of Business and The research results have good reference Social Science, 2(23), 147-158. value in solving one of the outstanding problems of the online shopping market in Ajzen, I. (1991). The Theory of Planned Vietnam. The research results also help Behavior. Organizational Behavior and online businesses have a more Human Decision Processes, 50(2), 179-121. Số 11 (2023): 29 – 44 41
Ajzen, I., & Fishbein, M. (1980). Journal of Asia Business Studies, 14(3), Understanding Attitudes and Predicting 281-306. Social Behavior. Englewood Cliffs, NJ: Gunawan, C., M., Rahmania, L., & Kenang, Prentice- Hall. I., H. (2023). The Influence of Social Al-Hattami, H., M., Abdullah, A., A., H., Al- Influence and Peer Influence on Intention Okaily, M., Al-Adwan, A., S., Al- To Purchase in E-Commerce. Review of Hakimi, M., A., & Haidar, F., T. (2023). Management and Entrepreneurship, 7(1), Determinants of interaction intention to 61-84. purchase online in less developed Ha, N., T., Nguyen, T., L., H., Pham, T., V., countries: The moderating role of & Nguyen, T., H., T., (2021). Factors technology infrastructure. Cogent Social Influencing Online Shopping Intention: Sciences, 9(1). An Empirical Study in Vietnam. Journal Al Hamli, S., S., & Sobaih, A., E., E. (2023). of Asian Finance, Economics and Factors Influencing Consumer Behavior Business, 8(3), 1257-1266. towards Online Shopping in Saudi Arabia Hair, J., F., Black, W., C., Babin, B., & Amid COVID-19: Implications for E- Anderson, R. (2010). Multivariate data Businesses Post Pandemic. Journal of analysis (7th editio). Prentice Hall. Risk and Financial Management, 16(1). Hatamifar, P., Ghader, Z., & Nikjoo, A. Aziz, N., N., A., & Wahid, N., A. (2018). (2021). Factors affecting international Why Consumers are Hesitant to Shop tourists’ intention to use local mobile Online: The Major Concerns towards apps in online purchase. Asia Pacific Online Shopping. International Journal Journal of Tourism Research, 26(12), of Academic Research in Business and 1285-1301. Social Sciences, 8(9), 1175-1185. Heijden, H. van der, Verhagen, T., & Binh, N., T., Anh, T., T., L., Hien, T., T., T., Creemers, M. (2003). Understanding Thao, L., T., Hang, T., P., N., & Hieu, N., online purchase intentions: contributions M. (2022). Factors influencing from technology and trust perspectives. continuance intention of online shopping European Journal of Information Systems of generation Y and Z during the new (2003), 12, 41-48. normal in Vietnam. Cogent Business and Management, 9(1). Hernández, B., Jiménez, J., & Martín, M., J. (2011). Age, gender and income: Do they Brusch, I., & Rappel, N. (2020). Exploring really moderate online shopping the acceptance of instant shopping – An behaviour? Online Information Review, empirical analysis of the determinants of 35(1), 113-133. user intention. Journal of Retailing and Hubert, M., Blut, M., Brock, C., Backhaus, C., Consumer Services, 54(May), 101936. & Eberhardt, T. (2017). Acceptance of Davis, F., D. (1989). Perceived Usefulness, Smartphone-Based Mobile Shopping: Perceived Ease of Use, and User Mobile Benefits, Customer Characteristics, Acceptance of Information Technology. Perceived Risks, and the Impact of MIS Quarterly, 13(3), 319-340. Application Context. Psychology and Dewi, C., K., Mohaidin, Z., & Murshid, M., Marketing, 34(2), 175-194. A. (2020). Determinants of online Igbaria, M., & Iivari, J. (1995). The effects of purchase intention: a PLS-SEM self-efficacy on computer usage. Omega, approach: evidence from Indonesia. 23(6), 587-605. 42 Số 11 (2023): 29 – 44
KHOA HỌC XÃ HỘI Juyal, S., A. (2018). An Empirical Study on Rita, P., Oliveira, T., & Farisa, A. (2019). Factors Influencing Shoppers’ Online The impact of e-service quality and Buying Behavior. International Journal customer satisfaction on customer of Online Marketing, 8(1), 55-79. behavior in online shopping. Heliyon, 5(10), e02690. Lodesso, S., L., van Niekerk, E., J., Jansen, C., A., & Müller, H. (2019). Student Sallam, M., A. (2016). The Impact of Brand Satisfaction Regarding Service Quality at Image and Corporate Branding on Ethiopian Public Higher Education Consumer’s Choice: The Role of Brand Institutions: A Case Study. Journal of Equity. International Journal of Student Affairs in Africa, 6(2). Marketing Studies, 8(1), 98. Maruping, L., M., Bala, H., Venkatesh, V., & Schepers, J., & Wetzels, M. (2007). A meta- Brown, S., A. (2016). Going Beyond analysis of the technology acceptance Intention: Integrating Behavioral model: Investigating subjective norm and Expectation Into the Unified Theory of moderation effects. Information and Acceptance and Use of Technology. Management, 44(1), 90-103. Journal of the Association for Shekhar, R., & Jaidev, U., P. (2020). Information Science and Technology, Antecedents of online purchase intention 68(3), 623-637. in the context of social commerce. Mei, Y., C., & Boon Aun, N. (2019). Factors International Journal of Applied Influencing Consumers’ Perceived Management Science, 12(1), 68-95. Usefulness of M-Wallet in Klang Valley, Shi Wen, T., Mohd Satar, N., Annizah Ishak, Malaysia. Integratove Business & N., & Ating, R. (2020). Finance and Economics, 8(4), 1-23. Business (IJAFB) eISSN: 0128-1844 Miranda, F., J., Rubio, S., Chamorro, A., & Malaysia. International Journal of Loureiro, S., M., C. (2014). Using social Accounting, 5(27), 93-117. networks sites in the purchasing decision Simon Kofi Dogbe, C., Zakari, M., & process. International Journal of E- Gregory Pesse-Kuma, A. (2019). Business Research, 10(3), 18-35. Perceived Online Risk, Consumer Trust Monsuwe´, T., P., Y., Dellaert, B., G., C., & and M-ShoppingBehaviour. Journal of Ruyter, K., de. (2004). What drives Social & Behavioural Research in consumers to shop online? A literature Business, 10(1), 10-23. review. International Journal of Service Stouthuysen, K., Teunis, I., Reusen, E., & Industry Management, 15(1), 102-121. Slabbinck, H. (2018). Initial trust and Pappas, I., O., Giannakos, M., N., & intentions to buy: The effect of vendor- Chrissikopoulos, V. (2012). Personalized specific guarantees, customer reviews and services in online shopping: Enjoyment the role of online shopping experience. and privacy. International Conference on Electronic Commerce Research and Information Society, i-Society 2012, May Applications, 27, 23-38. 2014, 168-173. Tham, K., W., Dastane, O., Johar, Z., & Puspitarini, D., A., Purnama, P., A., & Dewi, Ismail, N. (2019). Perceived Risk Factors I., R. (2021). Fraud risk and trust on the Affecting Consumers’ Online Shopping intention to buy of e-commerce. Journal Behaviour. The Journal of Asian Finance, of Contemporary Accounting, 3(1), 45-52. Economics and Business, 6(4), 246-260. Số 11 (2023): 29 – 44 43
Tham, K., W., Dastane, O., Johari, Z., & Xu, A., Li, W., Chen, Z., Zeng, S., Carlos, L. Ismail, N., B. (2019). Perceived risk A., & Zhu, Y. (2021). A Study of Young factors affecting consumers’ online Chinese Intentions to Purchase “Online shopping behaviour. Journal of Asian Paid Knowledge”: An Extended Finance, Economics and Business, 6(4), Technological Acceptance Model. 246-260. Frontiers in Psychology, 12(June), 1-13. Thang, H., N., & Lien, N., T., H. (2017). Xu, X., Wu, J., H., & Li, Q. (2020). What Factors inﬂuencing online shopping drives consumer shopping behavior in intention: an extension of the technology live streaming commerce? Journal of acceptance model. Hue University Electronic Commerce Research, 21(3), Journal of Science: Economics and 144-167. Development, 126(5B), 47-58. Yang, S., Lu, Y., Gupta, S., Cao, Y., & Venkatesh, V. (2000). Determinants of Zhang, R. (2012). Mobile payment perceived ease of use : integrating control, services adoption across time: An intrinsic motivation , acceptance model. empirical study of the effects of Inorganic Chemistry Communications, behavioral beliefs, social influences, and 11(3), 319-340. personal traits. Computers in Human Behavior, 28(1), 129-142. Ventre, I., & Kolbe, D. (2020). The Impact of Perceived Usefulness of Online Yoke Cheng, S., Alisa Hussain, I., Apparavu, Reviews, Trust and Perceived Risk on K., & Trianna Rosli, N. (2022). Factors Online Purchase Intention in Emerging Influencing Online Shopping Intention Markets: A Mexican Perspective. Journal Among Malaysians: a Quantitative-Based of International Consumer Marketing, Study. Electronic Journal of Business and 32(4), 287-299. Management, 7(3), 2550-1380. Weisberg, J., Te’eni, D., & Arman, L. Zhang, M., Qin, F., Wang, G., A., & Luo, C. (2011). Past purchase and intention to (2020). The impact of live video purchase in e-commerce: The mediation streaming on online purchase intention. of social presence and trust. Internet Service Industries Journal, 40(9–10), Research, 21(1), 82-96. 656-681. 44 Số 11 (2023): 29 – 44