Edelweiss Applied Science and Technology ISSN: 2576-8484 Vol. 9, No. 11, 101-113 2025 Publisher: Learning Gate DOI: 10.55214/2576-8484.v9i11.10792 © 2025 by the authors; licensee Learning Gate © 2025 by the authors; licensee Learning Gate History: Received: 22 August 2025; Revised: 2 October 2025; Accepted: 6 October 2025; Published: 30 October 2025 * Correspondence: lanutn@thanhdong.edu.vn Factors influencing the decision to choose online purchasing on multinational e-commerce platforms: A case study of Vietnamese consumers Le Van Hung1, Lan Ngoc Thi Uong2* 1,2Thanh Dong University, Hai Phong City, Vietnam; ahunglv@thanhdong.edu.vn (L.V.H.) blanutn@thanhdong.edu.vn (L.N.T.U.). Abstract: In the context of globalization and the rapid development of digital platforms, this study aims to understand the factors influencing Vietnamese consumers’ decisions to choose online purchasing on multinational e-commerce platforms. Quantitative research was conducted through a survey of 355 consumers. The data are analyzed in steps that include reliability testing of scales using Cronbach’s Alpha, as well as convergent and discriminant validity testing via exploratory factor analysis, followed by correlation and linear regression analyses. The results indicate that eight factors positively affect the decision to choose online purchasing on multinational e-commerce platforms among Vietnamese consumers, including facilitating conditions, habits, performance expectancy, perceived value, social influence, effort expectancy, beneficial motivation, and trust. The study provides insight into the current state of online consumption of Vietnamese consumers. Based on the analysis results, several implications are suggested to promote online purchasing on multinational e-commerce platforms in Vietnam. Keywords: Multinational e-commerce, Online purchasing, Vietnam. 1. Introduction Online purchasing has become a popular method of buying, which has widely developed from rural to urban areas [1]. According to statistics from the Ministry of Industry and Trade, Vietnam has over 41% of its population, nearly 50 million online shoppers, making it the highest in Southeast Asia. The transaction value is expected to reach 24 billion USD by 2025, with an average growth rate of 16 to 30% per year. The e-commerce and online purchasing market in Vietnam is experiencing significant development and has become the most attractive market in Southeast Asia. Therefore, online purchasing is a topic of interest to administrators and researchers. Currently, online purchasing in Vietnam operates not only domestically but also develops cross- border purchasing trends through multinational e-commerce platforms such as Shopee (Singapore), Lazada (China), TikTok Shop (China), Amazon (US), and AliExpress (China). Unlike domestic e- commerce platforms, multinational ones have several significant competitive advantages, including a global supply network, a diverse international product portfolio, technology to enhance the purchasing experience, and the capacity to utilize user data to personalize services. As a result, these e-commerce platforms occupy a substantial market share. They are reshaping the consumption habits of many Vietnamese consumers, especially young consumers, who tend to adopt global trends rapidly. Most studies on online purchasing, particularly in emerging markets like Vietnam, highlight the significant advantages of convenience, speed, time-saving, comparable prices, affordable choices, and entertainment that drive consumers to prefer online purchasing on e-commerce platforms. However, the analysis from the Vietnam E-commerce and Digital Economy Agency [2] reveals that around 44% of consumers view price as a barrier, 42% believe that the quality of online purchasing goods falls short of advertisements, and 33% express concerns about personal information security. Additionally, consumers worry about issues during the shipping phase, inadequate customer service, complicated payment 102 Edelweiss Applied Science and Technology ISSN: 2576-8484 Vol. 9, No. 11: 101-113, 2025 DOI: 10.55214/2576-8484.v9i11.10792 © 2025 by the authors; licensee Learning Gate processes, unprofessional websites, and troublesome online ordering. Despite this, empirical studies addressing these concerns comprehensively are quite limited. Therefore, this study aims to analyze the factors influencing the decision to choose online purchasing on multinational e-commerce platforms from the perspective of Vietnamese consumers. The research contributes to the growth of the e- commerce market in Vietnam, enhancing consumer experience and promoting sustainable development in the Vietnamese market. 2. Literature Review and Research Model 2.1. Multinational E-Commerce According to Turban et al. [3], e-commerce is the process of buying, selling, and exchanging products, services, and information through computer networks, including the Internet. In this process, information technology plays a crucial intermediary role in effectively supporting and executing commercial transactions, regardless of geographical distance or time. UNCTAD [4] defines e- commerce as the purchase and sale of goods and services conducted through computer networks using electronic means to place orders and make transactions. This definition indicates that e-commerce is not limited to retail platforms; it also encompasses business-to-business (B2B), business-to-consumer (B2C), consumer-to-consumer (C2C), and both government-to-business or citizen (G2B/G2C) transactions. In Vietnam, e-commerce involves the implementation of part or all commercial activities by electronic means [5]. This concept provides the legal foundation for developing commercial activities within the domestic digital environment. The United Nations Economic and Social Commission for Asia and the Pacific [6] argues that, based on the geographical location of the seller and the buyer, if the two parties involved in the transaction are from different countries, the transaction is classified as a multinational e-commerce transaction. According to Pham and Hoang [7], multinational e-commerce refers to the process of buying and selling goods and services that occur on an online platform, where sellers and buyers reside in different countries. Multinational e-commerce involves the purchase and sale of goods or services over the internet, with consumers in one country buying from sellers in another, encompassing the entire process from ordering and payment to the shipping or distribution of products and services internationally [8]. While Lu et al. [9] argue that multinational e-commerce is an extension of traditional e-commerce, in which international companies operate digital platforms to provide goods and services to global customers, often through exchanges such as Amazon, Alibaba, Shopee, and eBay. These enterprises have logistics infrastructure, data centers, payment systems, and customer care that cater to various national markets. 2.2. Online Purchasing According to Sulaiman et al. [10], online purchasing is the process by which consumers use technological devices such as computers, smartphones, and tablets with a network connection to access e-commerce websites or sales applications for searching, selecting, exchanging, and purchasing goods and services. These transactions take place at any time and in any location, without being bound by spatial or temporal limitations, greatly enhancing convenience and flexibility for consumers. According to Laudon and Traver [11], online purchasing is part of business-to-consumer (B2C) e-commerce, where customers use digital platforms to engage in the buying and selling of products and services without direct interaction with the seller. The application of digital technology in purchasing not only provides a convenient experience but also allows consumers to access richer information, easily compare prices, quality, and community reviews before making a purchase decision. Additionally, online purchasing is characterized by the non-physicality of interaction, high personalization through product suggestion systems, the expansion of cross-border purchasing opportunities, and the optimization of transaction costs by reducing spatial and personnel expenses [12]. This makes online purchasing not only an alternative form of commerce but also one that is gradually becoming the mainstream method in many countries, particularly in developing economies such as Vietnam. 103 Edelweiss Applied Science and Technology ISSN: 2576-8484 Vol. 9, No. 11: 101-113, 2025 DOI: 10.55214/2576-8484.v9i11.10792 © 2025 by the authors; licensee Learning Gate According to Solomon et al. [13], consumer behavior encompasses not only specific actions such as buying or using a product but also psychological and social factors that impact the consumer's decision- making process, including perception, motivation, attitudes, and accumulated consumer experience. Blackwell et al. [14] argue that consumer behavior involves all activities related to the search, collection, procurement, ownership, use, and post-purchase processing of goods or services. According to Kotler and Armstrong [15], consumer behavior is the set of actions that consumers take throughout the product search, evaluation, and selection process, as well as their reactions and feelings after purchasing. 2.3. Research Model The study employs the Unified Theory of Acceptance and Use of Technology (UTAUT) developed by Venkatesh et al. [16] to create a research model, UTAUT was formulated by synthesizing and inheriting several theories, including the Theory of Planned Behavior (TPB), the Technology Acceptance Model (TAM), and Innovation Diffusion Theory (IDT), to offer a more comprehensive and effective analytical framework for predicting human behavior regarding technology use. According to UTAUT, the acceptance and use of technology by individuals are influenced by four factors: performance expectancy, effort expectancy, social influence, and facilitating conditions. Furthermore, the author has provided an overview of several domestic studies related to the topic of online purchasing on e-commerce platforms by Pham and Hoang [7], Ta and Dang [17], Do et al. [18], Nguyen [19], Nguyen et al. [20], Mai [21] and Nguyen [22] to ensure alignment with the objectives and purpose of the research, based on a thorough evaluation of these studies and the Unified Theory of Acceptance and Use of Technology, the proposed research model is as follows: Figure 1. Research model. 2.4. Research Hypothesis Performance expectancy reflects the extent to which consumers believe that using e-commerce platforms will make purchasing more convenient, save them time and money, and improve the overall 104 Edelweiss Applied Science and Technology ISSN: 2576-8484 Vol. 9, No. 11: 101-113, 2025 DOI: 10.55214/2576-8484.v9i11.10792 © 2025 by the authors; licensee Learning Gate efficiency of consumer activity. It is derived from the concept of perceived usefulness in Davis' [23] TAM model, which assumes that users are willing to accept technology if they find it to be of practical benefit. Taylor and Todd [24] also argue that performance expectations are a key factor in predicting new technology usage behavior. In addition, according to Davis [25] motivational model: People with high motivation awareness of efficiency will actively seek and use online platforms to meet consumer needs. Based on the above arguments, the research hypothesis is proposed as follows: H1: Performance expectancy positively affects the decision to choose online purchasing on multinational e- commerce platforms. Effort expectancy reflects how easy it is for consumers to make online purchases through certain e- commerce platforms [16]. This concept is inherited from “perceived ease of use” in the TAM model [23] and “complexity” in the IDT model [26]. If consumers believe that searching, ordering, and paying on online platforms are simple, easy to navigate, and do not require much technical skill, they will tend to be more active in their purchasing behavior. Therefore, effort expectancy plays an important role in shaping and reinforcing online purchasing intentions. Based on the above arguments, the proposed research hypothesis is as follows: H2: Effort expectancy positively affects the decision to choose online purchasing on multinational e-commerce platforms. Social influence refers to the extent to which consumers are swayed by the opinions of influencers, such as friends, relatives, or colleagues, when making online purchasing decisions [16]. This factor stems from the concept of “subjective norms” in the TRA model [27] and the “social factor” in the MPCU model [28]. When the people around you encourage or use a certain e-commerce platform, consumers are likely to adopt that behavior to comply with social norms, thus increasing the intention to shop on the same platform. Based on the above arguments, the research hypothesis is proposed as follows: H3: Social influence positively affects the decision to choose online purchasing on multinational e-commerce platforms. Facilitating conditions reflect the extent to which consumers believe there is sufficient infrastructure and resources to conduct online purchasing easily and efficiently [16]. In the UTAUT and UTAUT2 models, this factor is recognized as an agent that directly influences the intention and behavior of technology usage. For online purchasing, facilitating conditions may include accessible devices (such as smartphones and computers), stable internet connections, user-friendly e-commerce platform interfaces, clear user manuals, prompt customer support services, as well as consumer digital knowledge and skills. When these conditions are met, consumers are likely to feel more confident in selecting and purchasing on e-commerce platforms. Based on the above arguments, the research hypothesis is proposed as follows: H4: Facilitating conditions positively affect the decision to choose online purchasing on multinational e- commerce platforms. Perceived value refers to the consumer's assessment of the trade-off between the benefits obtained and the costs associated with purchasing online through one or more e-commerce platforms [29]. It positively influences purchase intent when consumers believe that the value received, such as convenience, competitive pricing, and prompt service, exceeds the costs, including money, time, and effort. Certain e-commerce platforms can offer price advantages due to their large scale, optimized operations, and efficient logistics systems, which enhance perceived value and attract consumers [30]. Based on the above arguments, the research hypothesis is proposed as follows: H5: Perceived value positively affects the decision to choose online purchasing on multinational e-commerce platforms. Beneficial motivation refers to the joy, enjoyment, or sense of entertainment that consumers experience when engaging in online purchasing [31]. In the realm of information systems, it represents a form of cognitive enjoyment that directly influences the acceptance and use of technology [32]. For some consumers, particularly young people, interacting with modern and innovative e-commerce 105 Edelweiss Applied Science and Technology ISSN: 2576-8484 Vol. 9, No. 11: 101-113, 2025 DOI: 10.55214/2576-8484.v9i11.10792 © 2025 by the authors; licensee Learning Gate platforms can generate a fresh and exciting feeling, thus enhancing the intention to shop through these platforms. Based on the arguments presented above, the research hypothesis is proposed as follows: H6: Beneficial motivation positively affects the decision to choose online purchasing on multinational e- commerce platforms. Habits reflect the extent to which consumers engage in behaviors automatically and repeatedly over time [33]. The process of developing these habits is influenced by how much customers interact with and become familiar with online purchasing across various e-commerce platforms. Consumers who frequently use a particular e-commerce platform are more likely to incorporate its website or application into their daily routines. Consequently, habits not only help minimize confusion during the selection process but also enhance purchasing intentions on specific e-commerce platforms. Based on these points, the research hypothesis is proposed as follows: H7: Habits positively affect the decision to choose online purchasing on multinational e-commerce platforms. Trust is a crucial factor in conducting online transactions, playing a vital role in determining the success of the purchasing experience on e-commerce platforms. Numerous studies have confirmed that customer trust directly influences the acceptance and utilization of e-commerce services, akin to the usefulness and ease-of-use factors in the TAM model [34]. According to the Vietnam E-commerce and Digital Economy Agency [35], trust ranks among the key influences on consumers’ online purchasing decisions in Vietnam, alongside factors such as product or service quality and price. Consumers are willing to engage in transactions only when they are confident that the website will provide secure payment, that products are strictly monitored, and that customer service is trustworthy. Consequently, trust not only impacts purchasing decisions but also helps shape the intention to select an e-commerce platform in online consumer behavior. Based on the arguments presented, the proposed research hypothesis is as follows: H8: Trust positively affects the decision to choose online purchasing on multinational e-commerce platforms. 3. Methodology The preliminary scale is adapted from the UTAUT model by Venkatesh et al. [16] and the studies of Pham and Hoang [7], Ta and Dang [17], Do et al. [18], Nguyen [19], Nguyen et al. [20], Nguyen [22] and Mai [21]. Before incorporating the scale into the official survey, the author held a group discussion with several Vietnamese consumers who have made purchases on multinational e-commerce platforms, along with consulting some experts in the field of commerce, to recalibrate the scale to better align with the research audience and circumstances. At the conclusion of the discussion, experts strongly agreed with the proposed scale; however, some observed variables needed rephrasing. The study employed a 5-point Likert scale ranging from 1 (Strongly Disagree) to 5 (Strongly Agree). The formal scale comprises 32 observed variables corresponding to eight independent factors and one dependent factor. The study's sample size was calculated based on the recommendations of Hair et al. [36] using the optimal ratio of 10:1 for exploratory factor analysis; the required sample size is 320. However, the author distributed 380 questionnaires to account for any invalid responses that might negatively impact the results of the analysis. The study employs a convenient non-probability sampling method, targeting Vietnamese consumers who have successfully made purchases on multinational e- commerce platforms. As a result of the cleaning and removal of invalid questionnaires, a total of 355 valid questionnaires were obtained. Among the 355 surveyed Vietnamese consumers, 204 are female, representing 57.46%, while 151 are male, accounting for 42.54%. This data reflects the increasing trend of online purchasing among females. Regarding age distribution, individuals aged 18 to 24 constitute the largest segment with 174 respondents, representing 49.01%, followed by those aged 25 to 34 with 111 respondents (31.27%). Furthermore, individuals aged 35 to 44 and those aged 45 and above account for 10.14% and 6.20%, respectively, while the under-18 age group comprises 3.38%. In terms of occupation, students represent the largest sector with 143 respondents (40.28%), followed by office workers at 30.14%, self-employed individuals at 20.00%, and other occupations, which together make up 9.58%. Regarding online purchasing frequency, 241 individuals (67.89%) indicated that they shop online 106 Edelweiss Applied Science and Technology ISSN: 2576-8484 Vol. 9, No. 11: 101-113, 2025 DOI: 10.55214/2576-8484.v9i11.10792 © 2025 by the authors; licensee Learning Gate at least once per week. Conversely, 86 individuals (24.23%) purchase 2–3 times per month, and only 28 individuals (7.89%) reported purchasing less than once per month. In terms of the most frequently used e-commerce platform, Shopee emerges as the preferred choice with 160 respondents (45.07%), followed by Lazada with 89 respondents (25.07%) and TikTok Shop with 53 respondents (14.93%). Lastly, Amazon and AliExpress were chosen by 28 respondents (7.89%) and 25 respondents (7.04%), respectively. The study employed quantitative analysis using assays such as Cronbach’s Alpha, exploratory factor analysis (EFA), correlation analysis, and linear regression analysis, with a statistical significance level of 5 percent. The regression equation is expressed in a generalized form as follows: COP = β0 + β1*PE + β2*EE + β3*SI + β4*FC + β5*PV +β6*BM + β7*Hab+ β8*Tru +  In which: COS (dependent variable): decision to choose online purchasing on multinational e-commerce platforms Independent (Xi): Performance expectancy (PE), Effort expectancy (EE), Social influence (SI), Facilitating conditions (FC), Perceived value (PV), Beneficial motivation (BM), Habits (Hab), Trust (Tru). βk: Regression coefficients (k = 0, 1, 2....,8). 107 Edelweiss Applied Science and Technology ISSN: 2576-8484 Vol. 9, No. 11: 101-113, 2025 DOI: 10.55214/2576-8484.v9i11.10792 © 2025 by the authors; licensee Learning Gate 4. Results and Discussion Table 1. Reliability testing. Items Mean Cronbach’s Alpha Corrected Item-Total Correlation Cronbach’s Alpha if items deleted Performance expectancy PE1 4.05 0.809 0.482 0.751 PE2 0.450 0.740 PE3 0.431 0.735 PE4 0.426 0.724 Effort expectancy EE1 3.96 0.792 0.513 0.770 EE2 0.506 0.761 EE3 0.489 0.747 EE4 0.475 0.723 Social influence SI1 3.89 0.817 0.567 0.814 SI2 0.543 0.800 SI3 0.539 0.792 Facilitating conditions FC1 4.17 0.826 0.577 0.830 FC2 0.563 0.825 FC3 0.540 0.816 Perceived value PV1 3.78 0.797 0.491 0.752 PV2 0.476 0.748 PV3 0.462 0.735 PV4 0.455 0.727 Beneficial motivation BM1 3.91 0.813 0.514 0.808 BM2 0.496 0.792 BM3 0.473 0.771 Habits Hab1 4.23 0.831 0.562 0.826 Hab2 0.543 0.814 Hab3 0.530 0.803 Hab4 0.521 0.789 Trust Tru1 3.94 0.820 0.596 0.811 Tru2 0.573 0.805 Tru3 0.541 0.790 Tru4 0.529 0.786 Decision to choose online purchasing on multinational e-commerce platforms COP1 4.10 0.818 0.629 0.807 COP2 0.618 0.799 COP3 0.605 0.781 The reliability test results show that the scales in the model have a Cronbach’s Alpha greater than 0.7, satisfying the requirements set by Hair et al. [36]. Additionally, observed variables with a total variable correlation coefficient greater than 0.3 demonstrated a positive contribution to the scale. Furthermore, since the Cronbach’s Alpha if items deleted is smaller than the overall Cronbach’s Alpha, this indicates that none of the observed variables diminish the overall reliability of the scale, making it appropriate to retain all the observed variables. Thus, the independent scales are reliable, meeting the conditions for conducting subsequent analyses [36]. 108 Edelweiss Applied Science and Technology ISSN: 2576-8484 Vol. 9, No. 11: 101-113, 2025 DOI: 10.55214/2576-8484.v9i11.10792 © 2025 by the authors; licensee Learning Gate Table 2. Results of the EFA of independent factors. KMO = 0.819 Bartlett’s Test Approx. Chi-Square 9887.562 df 389 Sig. 0.000 Items Factor 1 2 3 4 5 6 7 8 EE1 0.816 EE2 0.802 EE3 0.793 EE4 0.771 FC1 0.808 FC2 0.797 FC3 0.785 Hab1 0.829 Hab2 0.810 Hab3 0.789 Hab4 0.778 SI1 0.794 SI2 0.781 SI3 0.769 Tru1 0.811 Tru2 0.807 Tru3 0.791 Tru4 0.786 BM1 0.802 BM2 0.783 BM3 0.758 PE1 0.799 PE2 0.780 PE3 0.776 PE4 0.755 PV1 0.822 PV2 0.817 PV3 0.804 PV4 0.793 % of Variance 31.759 42.091 48.725 55.313 59.186 63.497 70.126 79.854 Eigenvalue 7.314 6.988 6.127 5.793 4.617 3.528 2.796 1.350 The results of the exploratory factor analysis of the independent factors show that the KMO coefficient is 0.819 (> 0.5), indicating that the data are suitable for factor analysis. Bartlett's test has a significance value of 0.000, which is statistically significant, confirming that the factors have a strong enough correlation for analysis. Additionally, the rotation matrix extracted 8 factors with Eigenvalues > 1, explaining 79.854% of the variability in the data, indicating a high level of explanation and relevance in the study. Furthermore, the factor loadings of the observed variables are > 0.7, confirming that the level of convergence is good and that no variables are excluded from the measurement scale. The groups of variables are clearly separated by each factor, as the research model proposes. Therefore, the EFA results indicate that the independent scales exhibit good convergence and discriminant validity, making them suitable for further analyses [36]. 109 Edelweiss Applied Science and Technology ISSN: 2576-8484 Vol. 9, No. 11: 101-113, 2025 DOI: 10.55214/2576-8484.v9i11.10792 © 2025 by the authors; licensee Learning Gate Table 3. Results of the EFA of the dependent scale. KMO = 0.821 Bartlett’s Test Approx. Chi-Square 239.157 df 3 Sig. 0.000 Scale No. Factor loading Decision to choose online purchasing on multinational e-commerce platforms COP1 0.803 COP2 0.795 COP3 0.784 % of Variance 80.113 Eigenvalue 1.982 The EFA result of the dependent scale indicated that the KMO coefficient was 0.821, satisfying the condition of being greater than 0.5 and less than 1, which proves that the data are suitable for factor analysis. Bartlett's test yielded a significance level of 0.000, confirming that the correlation between the observed variables is sufficiently strong to justify further exploration of the factors. The three observed variables of the scale have high factor loading coefficients, ranging from 0.784 to 0.803, and converge into a single group of factors, with an Eigenvalue of 1.982, explaining a total variance of 80.113%. This indicates that this factor accounts for 80.113% of the variability in the data, demonstrating the scale’s high reliability. Therefore, the dependent scale meets the criteria for reliability, convergent validity, and unidimensional validity [36]. Table 4. Correlation analysis. COS PE EE SI FC PV BM Hab Tru COS 1 PE 0.737** 1 EE 0.692** 0.213** 1 SI 0.780** 0.174* 0.241** 1 FC 0.714** 0.256** 0.188** 0.192** 1 PV 0.759** 0.198** 0.253* 0.205* 0.189** 1 BM 0.683** 0.209** 0.179** 0.187** 0.216** 0.28* 1 Hab 0.717** 0.235* 0.202** 0.234** 0.192* 0.335** 0.419** 1 Tru 0.675** 0.210** 0.2** 0.234** 0.192* 0.335** 0.419** 0.192* 1 Note: *significant at p < 0.05, **significant at p < 0.01. The results of the correlation analysis indicate a strong correlation between independent and dependent factors, with a correlation coefficient greater than 0.5 and a significance value less than 0.05, ensuring statistical significance. Additionally, there is clear evidence of multicollinearity among the independent factors, which meets the conditions for regression analysis [36]. Table 5. Summary model. Model R R2 Adjusted R2 Std. Error of the Estimate Durbin-Watson 1 0.815 0.806 0.798 0.315 1.887 The results of the multivariate linear regression analysis indicate that the research model achieved high relevance and statistical significance, with an R of 0.815, reflecting a close relationship between the independent and dependent factors. The R² is 0.823, and the adjusted R² is 0.806, demonstrating that the independent factors in the model account for up to 80.6% of the variability of the dependent factor. The analysis results also show that the Durbin-Watson coefficient of 1.887 falls between 1.5 and 2.5, indicating no residual autocorrelation in the regression model. Furthermore, the results of the ANOVA 110 Edelweiss Applied Science and Technology ISSN: 2576-8484 Vol. 9, No. 11: 101-113, 2025 DOI: 10.55214/2576-8484.v9i11.10792 © 2025 by the authors; licensee Learning Gate analysis and F-test reveal that the statistical value has a Sig value of 0.000, confirming that the linear regression model is appropriate for the data file and can be utilized. Table 6. Linear regression results. Model Unstandardized Coefficients Standardized Coefficients t Sig. Collinearity Statistics B SD Beta Tolerance VIF 1 Constant 0.287 0.027 5.193 0.001 PE 0.260 0.018 0.298 4.538 0.000 0.682 1.792 EE 0.203 0.010 0.215 5.740 0.002 0.591 1.834 SI 0.229 0.011 0.246 3.972 0.000 0.633 1.751 FC 0.328 0.026 0.355 5.857 0.000 0.574 1.820 PV 0.241 0.020 0.267 4.612 0.001 0.610 1.743 BM 0.187 0.019 0.192 3.988 0.000 0.645 1.707 Hab 0.294 0.023 0.301 4.521 0.004 0.593 1.856 Tru 0.169 0.015 0.183 5.119 0.000 0.588 1.715 The results of the validation of the research hypotheses indicated that the independent factors in the regression model had a significance value of less than 0.05, demonstrating that the model was statistically significant and that the independent factors significantly influenced the dependent variable. Additionally, the Variance Inflation Factors (VIF) were below 2, confirming that there was no multicollinearity among the variables, which supports the stability and reliability of the regression estimates. Diagnostic tests for the regression, including scatterplots, histograms, and P-P plots, verified that the fundamental assumptions of multivariate linear regression were satisfied. The scatter plot of residuals versus predicted values showed a random distribution of points around the horizontal axis, indicating no clear pattern or trend, thus confirming the assumptions of linearity and homoscedasticity. The histogram of residuals approximated a normal distribution, with a mean close to zero and a standard deviation near 1, suggesting that the residuals did not exhibit significant deviations. Furthermore, the P-P plot of normalized residuals demonstrated that the data points closely followed the diagonal line, indicating conformity with the normal distribution and further validating the reliability of the regression model used. Table 7. Hypothesis testing. Hypothesis Relationship Results H1 Performance expectancy positively influences the decision to select online purchasing on multinational e-commerce platforms. Supported H2 Effort expectancy positively influences the decision to select online purchasing on multinational e-commerce platforms. Supported H3 Social influence positively affects the decision to choose online purchasing on multinational e-commerce platforms. Supported H4 Facilitating conditions positively influence the decision to select online purchasing on multinational e-commerce platforms. Supported H5 Perceived value positively influences the decision to select online purchasing on multinational e-commerce platforms. Supported H6 Beneficial motivation positively affects the decision to choose online purchasing on multinational e-commerce platforms. Supported H7 Habits positively affect the decision to choose online purchasing on multinational e- commerce platforms. Supported H8 Trust positively affects the decision to choose online purchasing on multinational e- commerce platforms. Supported Thus, the accepted research hypotheses are all less than 0.05 and support the Unified Theory of Acceptance and Use of Technology (UTAUT). The results of this study align with those of Taylor and 111 Edelweiss Applied Science and Technology ISSN: 2576-8484 Vol. 9, No. 11: 101-113, 2025 DOI: 10.55214/2576-8484.v9i11.10792 © 2025 by the authors; licensee Learning Gate Todd [24], Venkatesh et al. [16], Chiu et al. [30], and Thong et al. [32]. The distinction between the findings of this study and those of earlier research lies in its emphasis on facilitating conditions and habits of consumers, whereas previous studies focused on perceived usefulness and perceived ease of use. Additionally, the study highlights perceived value in influencing consumers’ online purchasing choices. This distinction reflects the specific characteristics of Vietnamese consumers. The standardized linear regression equation is defined as follows: COP = 0.355*FC + 0.301*Hab + 0.298*PE + 0.267*PV + 0.246*SI + 0.215*EE + 0.192*BM + 0.183*Tru +  Furthermore, the results of the Independent Samples T-test and One-Way ANOVA analysis indicate that there are statistically significant differences among certain demographic groups regarding Vietnamese consumers’ online shopping behavior on multinational e-commerce platforms. The T-test results based on gender showed a significance value of < 0.05, reflecting a difference between males and females. This finding suggests that gender may influence consumer behavior, with females tending to use online shopping more than males. The ANOVA tests by age, occupation, and various comparison groups also yielded significance values below 0.05, indicating significant differences among these groups. Younger consumers, particularly those aged 18 to 24, including students and office workers, are more inclined to choose online shopping than other groups. This trend can be attributed to their access to advanced technology, adaptability in consumer behavior, and familiarity with international e- commerce platforms. 5. Conclusions and Implications This study identified factors influencing the decision of Vietnamese consumers to choose online purchasing on multinational e-commerce platforms, including facilitating conditions, habits, performance expectancy, perceived value, social influence, effort expectancy, beneficial motivation, and trust. Based on the study's findings, several management implications are suggested to enhance the decision-making process for online purchasing on multinational e-commerce platforms among Vietnamese consumers as follows: First, e-commerce platforms must continue to create favorable conditions for consumers during their service experience by optimizing the user interface, simplifying ordering and payment processes, ensuring stable connections, and providing effective customer support. Additionally, it is essential to invest in infrastructure technology and AI applications to suggest appropriate products and enhance system performance, thereby improving satisfaction throughout the shopping journey. Second, e-commerce platforms should concentrate on developing and sustaining customers’ online shopping habits through loyalty programs, periodic incentives, personalized shopping recommendations, straightforward notifications, and an intuitive interface. Establishing a regular and consistent experience will help consumer behavior integrate into the customer’s daily routine. Third, e-commerce platforms must elevate efficiency expectations by enhancing communication about the benefits customers receive, such as time savings, product diversity, competitive prices, and the ability to quickly look up and review options. Investing in support tools, such as chatbots, detailed instructions, and prompt responses, also helps to raise awareness of the platform’s effectiveness. Fourth, e-commerce platforms must create a reasonable cost value for customers by implementing flexible pricing strategies, offering free shipping, providing discount codes, establishing refund policies, and ensuring transparent price comparisons between sellers, which helps consumers feel that the cost is justified. It will improve their intention to use the platform. Fifth, e-commerce platforms should leverage KOLs, reputable reviewers, or existing customers to disseminate brand messages. They should develop programs that encourage experience sharing, post- purchase evaluations, incentives for referring friends, and promote social imitation behavior. Sixth, platforms need to be established to ensure that the procurement process is straightforward, easy to navigate, and less step-by-step. Provide clear instructions, a minimalist interface, and support in Vietnamese, especially for older or less tech-savvy users. 112 Edelweiss Applied Science and Technology ISSN: 2576-8484 Vol. 9, No. 11: 101-113, 2025 DOI: 10.55214/2576-8484.v9i11.10792 © 2025 by the authors; licensee Learning Gate Seventh, focus on creating an engaging shopping experience by organizing themed events, hosting creative sales livestreams, implementing point games, or designing lively interfaces. This approach transforms shopping from a mere necessity into a source of entertainment. Finally, e-commerce platforms must ensure the confidentiality of customer information, maintain transparent return policies, enforce strict seller management, and promptly handle complaints. The public evaluation of sellers, product authentication, and the use of "censored" symbols also contribute to strengthening customer trust. Transparency: The authors confirm that the manuscript is an honest, accurate, and transparent account of the study; that no vital features of the study have been omitted; and that any discrepancies from the study as planned have been explained. This study followed all ethical practices during writing. Copyright: © 2025 by the authors. This article is an open-access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/). References [1] V. H. Pham, T. A. T. Duong, and T. M. T. Pham, "Factors impact on the intention online shopping of Quang Ngai consumers," Journal of Finance – Marketing, vol. 14, no. 4, pp. 100–112, 2023. [2] Vietnam E-commerce and Digital Economy Agency, Vietnam E-commerce white book 2021. Hanoi, Vietnam: Ministry of Industry and Trade, 2021. [3] E. Turban, J. Outland, D. King, J. K. Lee, T.-P. Liang, and D. C. Turban, Electronic commerce 2018: A managerial and social networks perspective. Cham, Switzerland: Springer, 2017. [4] UNCTAD, "UNCTAD B2C E-commerce index 2020: Spotlight on Latin America and the Caribbean, United Nations Conference on Trade and Development," 2020. https://unctad.org/ [5] National Assembly, Law on electronic transactions. Hanoi, Vietnam: Vietnam National Assembly Publishing House, 2005. [6] United Nations Economic and Social Commission for Asia and the Pacific, Economic and social survey of Asia and the Pacific 2020: Towards sustainable economies. Bangkok, Thailand: United Nations, 2020. [7] H. C. Pham and N. B. C. Hoang, "Determinants of e-commerce platform selection intention of young Vietnamese generations when purchasing goods overseas," Journal of International Economics and Management, vol. 138, pp. 82– 103, 2021. [8] Organisation for Economic Co-operation and Development (OECD), "Unpacking e-commerce: Business models, trends and policies," OECD Digital Economy Papers (No. 304). OECD Publishing, Paris, France, 2019. [9] Y. Lu, L. Zhao, and B. Wang, "From virtual community members to C2C e-commerce buyers: Trust in virtual communities and its effect on consumers’ purchase intention," Electronic Commerce Research and Applications, vol. 9, no. 4, pp. 346-360, 2010. https://doi.org/10.1016/j.elerap.2009.07.003 [10] Y. Sulaiman, M. M. Yusr, and K. A. Ismail, "The influence of marketing mix and perceived risk factors on online purchase intentions," International Journal of Research in Business Studies and Management, vol. 4, no. 9, pp. 30-40, 2017. [11] K. C. Laudon and C. G. Traver, E-commerce: Business, technology, society. Boston, MA, USA: Addison-Wesley, 2002. [12] S. Hassan, R. Rashid, and F. Li, "Utilising modified utaut to understand students' online shopping behaviour: A case of e-retail co-operative website in malaysia," Journal of Electronic Commerce in Organizations (JECO), vol. 13, no. 4, pp. 74-90, 2015. https://doi.org/10.4018/JECO.2015100104 [13] M. Solomon, G. J. Bamossy, S. Askegaard, and M. K. Hogg, Consumer behaviour: A European perspective, 3rd ed. Harlow, England: Prentice Hall, 2006. [14] R. D. Blackwell, P. W. Miniard, and J. F. Engel, Consumer behavior. Fort Worth, TX, USA: Harcourt College Publishers, 2001. [15] P. Kotler and G. Armstrong, Principles of marketing, 16th ed. Harlow, England: Pearson, 2016. [16] V. Venkatesh, M. G. Morris, G. B. Davis, and F. D. Davis, "User acceptance of information technology: Toward a unified view1," MIS Quarterly, vol. 27, no. 3, pp. 425-478, 2003. https://doi.org/10.2307/30036540 [17] V. Ta and X. Dang, "Factors influences Z generation consumer purchase intentions in E-commerce in Vietnam," Journal of Banking Science and Training, vol. 229, no. 6, pp. 27-35, 2021. [18] V. H. Do, P. T. Nguyen, T. N. A. Nguyen, T. L. Ngo, and T. D. Nguyen, "Factors affecting young people’s decisions towards online shopping," Scientific Journal – Hanoi Metropolitan University, vol. 52, pp. 92–103, 2021. https://creativecommons.org/licenses/by/4.0/ https://unctad.org/ https://doi.org/10.1016/j.elerap.2009.07.003 https://doi.org/10.4018/JECO.2015100104 https://doi.org/10.2307/30036540 113 Edelweiss Applied Science and Technology ISSN: 2576-8484 Vol. 9, No. 11: 101-113, 2025 DOI: 10.55214/2576-8484.v9i11.10792 © 2025 by the authors; licensee Learning Gate [19] K. Q. T. Nguyen, "Research on factors influencing consumers’ online shopping behavior," Economy & Forecast Review, vol. 30, pp. 45-48, 2023. [20] T. T. Nguyen, T. N. L. Pham, D. T. Le, and N. H. V. Truong, "Study the factors affecting consumer shopping behavior on Shopee E-commerce channel of students in Da Nang city," DTU Journal of Science and Technology, vol. 2, no. 57, pp. 115-124, 2023. [21] H. T. Mai, "Online shopping trends of Vietnamese consumers," Industry and Trade Magazine, vol. 4, pp. 10-14, 2023. [22] X. V. Nguyen, "Factors affecting the shopping decisions of students at Ho Chi Minh City University of Technology and Education on e-commerce platforms," Industry and Trade Magazine, vol. 15, pp. 30-34, 2024. [23] F. D. Davis, "Perceived usefulness, perceived ease of use, and user acceptance of information technology," MIS Quarterly, vol. 13, no. 3, pp. 319-340, 1989. https://doi.org/10.2307/249008 [24] S. Taylor and P. A. Todd, "Understanding information technology usage: A test of competing models," Information Systems Research, vol. 6, no. 2, pp. 144-176, 1995. https://doi.org/10.1287/isre.6.2.144 [25] F. D. Davis, "User acceptance of information technology: System characteristics, user perceptions and behavioral impacts," International Journal of Man-Machine Studies, vol. 38, no. 3, pp. 475-487, 1993. https://doi.org/10.1006/imms.1993.1022 [26] E. M. Rogers, Diffusion of innovations, 4th ed. New York, NY, USA: The Free Press, 1995. [27] M. Fishbein and I. Ajzen, Belief, attitude, intention, and behavior: An introduction to theory and research. Reading, MA, USA: Addison-Wesley, 1975. [28] R. L. Thompson, C. A. Higgins, and J. M. Howell, "Personal computing: Toward a conceptual model of utilization," MIS Quarterly, vol. 15, no. 1, pp. 125-143, 1991. https://doi.org/10.2307/249443 [29] V. A. Zeithaml, "Consumer perceptions of price, quality, and value: A means-end model and synthesis of evidence," Journal of Marketing, vol. 52, no. 3, pp. 2-22, 1988. https://doi.org/10.1177/002224298805200302 [30] C. M. Chiu, E. T. Wang, Y. H. Fang, and H. Y. Huang, "Understanding customers' repeat purchase intentions in B2C e‐commerce: The roles of utilitarian value, hedonic value and perceived risk," Information Systems Journal, vol. 24, no. 1, pp. 85-114, 2014. https://doi.org/10.1111/j.1365-2575.2012.00407.x [31] H. Van der Heijden, "User acceptance of hedonic information systems," MIS Quarterly, vol. 28, no. 4, pp. 695-704, 2004. https://doi.org/10.2307/25148660 [32] J. Y. Thong, S.-J. Hong, and K. Y. Tam, "The effects of post-adoption beliefs on the expectation-confirmation model for information technology continuance," International Journal of Human-Computer Studies, vol. 64, no. 9, pp. 799-810, 2006. https://doi.org/10.1016/j.ijhcs.2006.05.001 [33] M. Limayem, S. G. Hirt, and C. M. Cheung, "How habit limits the predictive power of intention: The case of information systems continuance," MIS Quarterly, vol. 31, no. 4, pp. 705-737, 2007. https://doi.org/10.2307/25148817 [34] D. Gefen, E. Karahanna, and D. W. Straub, "Trust and TAM in online shopping: An integrated model," MIS Quarterly, vol. 27, no. 1, pp. 51-90, 2003. https://doi.org/10.2307/30036519 [35] Vietnam E-commerce and Digital Economy Agency, Vietnam E-commerce white book 2020. Hanoi, Vietnam: Ministry of Industry and Trade, 2020. [36] J. F. Hair, W. C. Black, B. J. Babin, and R. E. Anderson, Multivariate data analysis, 7th ed. New York: Pearson, 2010. https://doi.org/10.2307/249008 https://doi.org/10.1287/isre.6.2.144 https://doi.org/10.1006/imms.1993.1022 https://doi.org/10.2307/249443 https://doi.org/10.1177/002224298805200302 https://doi.org/10.1111/j.1365-2575.2012.00407.x https://doi.org/10.2307/25148660 https://doi.org/10.1016/j.ijhcs.2006.05.001 https://doi.org/10.2307/25148817 https://doi.org/10.2307/30036519