Các yếu tố tác động đến ý định sử dụng thanh toán điện tử của người tiêu dùng ở tây ninh

BỘ GIÁO DỤC VÀ ĐÀO TẠO TRƯỜNG ĐẠI HỌC SƯ PHẠM KỸ THUẬT THÀNH PHỐ HỒ CHÍ MINH LUẬN VĂN THẠC SĨ BÙI THỊ MỸ TIÊN CÁC YẾU TỐ TÁC ĐỘNG ĐẾN Ý ĐỊNH SỬ DỤNG THANH TOÁN ĐIỆN TỬ CỦA NGƯỜI TIÊU DÙNG Ở TÂY NINH NGÀNH: QUẢN LÝ KINH TẾ Tp Hồ Chí Minh, tháng 11/2022 BỘ GIÁO DỤC VÀ ĐÀO TẠO TRƯỜNG ĐẠI HỌC SƯ PHẠM KỸ THUẬT TP HỒ CHÍ MINH KHOA KINH TẾ LUẬN VĂN THẠC SỸ BÙI THỊ MỸ TIÊN CÁC YẾU TỐ TÁC ĐỘNG ĐẾN Ý ĐỊNH SỬ DỤNG THANH TOÁN ĐIỆN TỬ CỦA NGƯỜI TIÊU DÙNG Ở TÂY NINH NGÀNH: QUẢN LÝ KINH TẾ - 8340410 Người hướng dẫn khoa học: TS NGUYỄN THỊ THANH VÂN TP HCM, Tháng 08 năm 2022 i QUYẾT ĐỊNH GIAO ĐỀ TÀI ii LÝ LỊCH KHOA HỌC I LÝ LỊCH SƠ LƯỢC − Họ tên: Bùi Thị Mỹ Tiên − Giới tính: Nữ − Ngày, tháng, năm sinh: 17/02/1989 − Nơi sinh: Tây Ninh − Quê quán: Trà Vinh − Dân tộc: Kinh − Địa liên lạc: số hẻm 24, đường Trịnh Phong Đán, xã Trường Tây, thị xã Hòa Thành, Tây Ninh − Điện thoại di động: 0934054564 − E-mail: mytien172@gmail.com II QUÁ TRÌNH ĐÀO TẠO Đại học − Hệ đào tạo: Tập trung − Thời gian đào tạo từ: 1/2007 đến 1/2011 − Nơi học: Trường đại học Sư Phạm Kỹ Thuật Thành phố Hồ Chí Minh − Ngành học: Quản lý cơng nghiệp III Q TRÌNH CƠNG TÁC CHUN MƠN KỂ TỪ KHI TỐT NGHIỆP ĐẠI HỌC Thời gian 09/2012 đến Nơi công tác Công việc đảm nhận Trường Trung Cấp Kinh Tế Kỹ Giáo viên Thuật Tây Ninh Tôi cam đoan thật./ Ngày 01 tháng 08 năm 2022 Người thực Bùi Thị Mỹ Tiên iii LỜI CAM ĐOAN Tôi xin cam đoan công trình nghiên cứu tơi Ngoại trừ tài liệu tham khảo trích dẫn luận văn này, tơi cam đoan toàn phần hay phần nhỏ luận văn chưa công bố sử dụng để nhận cấp nơi khác Xin chân thành cảm ơn trân trọng! Ngày 01 tháng 08 năm 2022 Người thực Bùi Thị Mỹ Tiên iv LỜI CẢM ƠN Tôi xin chân thành cảm ơn TS Nguyễn Thị Thanh Vân, quý thầy, cô giảng dạy khoa đào tạo sau đại học, Đại học Sư phạm Kỹ thuật thành phố Hồ Chí Minh tận tình truyền đạt kiến thức, kinh nghiệm hướng dẫn lý thuyết triển khai thực tế để tơi hồn thành đề tài “Các yếu tố tác động đến ý định sử dụng toán điện tử người tiêu dùng Tây Ninh” Bên cạnh đó, tơi xin trân trọng gửi lời cảm ơn chân thành đến anh/chị/em dành thời gian hỗ trợ tham gia khảo sát cung cấp ý kiến đóng góp hỗ trợ tơi q trình thực luận văn Trong q trình thực luận văn cịn nhiều thiếu sót, mong nhận thơng cảm từ phía thầy Thêm vào đó, tơi ln hi vọng nhận góp ý chân thành từ Q thầy để tơi hồn thiện kiến thức kinh nghiệm thân Cuối xin kính chúc q Thầy Cơ Trường Đại học Sư phạm Kỹ thuật Thành phố Hồ Chí Minh dồi sức khỏe gặt hái nhiều thành công công việc sống Xin chân thành cảm ơn! Ngày 01 tháng 08 năm 2022 Người thực Bùi Thị Mỹ Tiên v TĨM TẮT Mục đích nghiên cứu xác định yếu tố ảnh hưởng đến ý định sử dụng toán điện tử người tiêu dùng Tây Ninh Và bên cạnh đó, cịn kiểm định có khác biệt độ tuổi, giới tính, trình độ, nghề nghiệp, thu nhập người tiêu dùng Tây Ninh việc chấp nhận sử dụng toán điện tử Các phương pháp sử dụng nghiên cứu để kiểm tra giả thuyết: định tính (để xác định thang đo thức từ việc vấn chuyên sâu người am hiểu toán điện tử từ thang đo nháp) định lượng (để kiểm chứng lại thang đo thức) Mẫu phát 200 người, sau thu thập gạn lọc cịn lại 170 mẫu hợp lệ, sau sử dụng phần mềm SPPS 20, phân tích độ tin cậy theo Cronbach’s Alpha nhân tố khám phá EFA thực hồi quy tuyến tính để kiểm định tác động yếu tố Kết nghiên cứu xác định: - Phương trình hồi quy là: SD = 0,256 * XH + 0,253 * HQ + 0,321*DK – 0,179 * RR + 0,151 * DM - Yếu tố ảnh hưởng đến ý định sử dụng toán điện tử người tiêu dùng Tây Ninh gồm: đồng biến với biến Ảnh hưởng xã hội, Kỳ vọng hiệu quả, Điều kiện thuận lợi Sự đổi người sử dụng nghịch biến với biến Nhận thức rủi ro - Mặt khác, với số mẫu quan sát, khơng có khác biệt có ý nghĩa thống kê ý định sử dụng tốn điện tử đáp viên có giới tính, độ tuổi, mức thu nhập, nơi sinh sống khác vi ABTRACT The research has achieved its goal of identifying which factors affect consumer’s intention to use E-payment adoption in Tay Ninh province Beside that, there have accreditation about any differentiation about age, gender, education, occupation, income, … with consumers’ intention to use Epayment adoption in Tay Ninh province A survey method approach is employed to examine posited hypotheses: quantitative method (to determine official scale from draft scale by in depth interview the persons who are have high awareness about E-payment) and quantitative method (to determine official scale) Research investigating the original sample size is 200 persons, after surveying with a sample size of 170 observations, the study used SPSS20, analyze based on Cronbach’s Alpha and EFA as well as regression liner The results of research show that: - Regression liner: SD = 0,256 * XH + 0,253 * HQ + 0,321*DK – 0,179 * RR + 0,151 * DM => Among that, factors affect to Consumers’ intention use Epayment adoption: have positive relationship with Social influence, Performance expectancy, Facilitating conditions and Personal Innovativeness and negative relation with Perceived Risk - However, with measured sample size, there is no difference significantly about gender, age, income, living to Consumers’ intention to use E-payment adoption vii MỤC LỤC QUYẾT ĐỊNH GIAO ĐỀ TÀI I LÝ LỊCH KHOA HỌC II LỜI CAM ĐOAN III LỜI CẢM ƠN IV TÓM TẮT V ABTRACT VI MỤC LỤC VII DANH MỤC TỪ VIẾT TẮT XI DANH MỤC BẢNG XIII DANH MỤC HÌNH XV CHƯƠNG 1: GIỚI THIỆU 1.1 Lý chọn đề tài: 1.2 Mục tiêu nghiên cứu 1.3 Đối tượng nghiên cứu: 1.4 Phạm vi nghiên cứu: 1.5 Phương pháp nghiên cứu: 1.6 Đóng góp luận văn: 1.7 Kết cấu luận văn: CHƯƠNG 2: TỔNG QUAN LÝ THUYẾT 2.1.1 Khái niệm toán điện tử 2.1.2 Hạ tầng toán điện tử Việt Nam 2.1.3 Các phương thức toán điện tử 2.1.3.1 Thanh toán thẻ: 2.1.3.2 Thanh toán qua cổng: 10 2.1.3.3 Thanh toán ví điện tử 10 2.1.3.4 Thanh toán thiết bị điện thoại thông minh 11 2.2 Lợi ích tốn điện tử 12 2.3 Tổng quan mơ hình nghiên cứu liên quan đến đề tài 14 viii 2.3.1 Mơ hình Chấp nhận cơng nghệ (Technology Acceptance Model TAM) 14 2.3.2 Mơ hình đồng việc chấp nhận sử dụng công nghệ (UTAUT) 15 2.4 Các cơng trình nghiên cứu có liên quan 17 2.4.1 Các nghiên cứu giới 17 2.4.2 Các nghiên cứu nước 19 2.5 Đề xuất mơ hình nghiên cứu 22 CHƯƠNG 3: THIẾT KẾ NGHIÊN CỨU 26 3.1 Quy trình nghiên cứu 26 3.2 Thiết kế nghiên cứu 27 3.2.1 Xác định thang đo 27 3.2.2 Nghiên cứu định tính 29 3.2.3 Kết nghiên cứu định tính mã hóa nhân tố biến 29 3.3 Phương pháp nghiên cứu định lượng: 32 3.3.1 Phương pháp chọn mẫu nghiên cứu: 32 3.3.2 Phương pháp xác định cỡ mẫu: 32 3.3.3 Phương pháp phân tích liệu: 32 3.3.3.1 Thống kê mô tả: 32 3.3.3.2 Kiểm tra độ tin thang đo hệ số Cronbach’s Alpha: 32 3.3.3.3 Phân tích nhân tố khám phá EFA: 33 3.3.3.4 Phân tích hồi quy đa biến: 33 CHƯƠNG 4: KẾT QUẢ NGHIÊN CỨU 36 4.1 Mô tả đặc điểm mẫu nghiên cứu: 36 4.1.1 Mô tả biến định danh 36 4.1.1.1 Giới tính 36 4.1.1.2 Độ tuổi 36 4.1.1.3 Mức thu nhập 37 4.1.1.4 Trình độ học vấn 37 4.1.1.5 Nghề nghiệp 38 4.1.1.6 Nơi sinh sống 38 xxiv Residuals Statisticsa Minimum Maximum Mean Std Deviation N Predicted Value 1.5958 4.7562 3.2576 0.57381 170 Residual -1.16751 1.72203 0.00000 0.52166 170 Std Predicted Value -2.896 2.612 0.000 1.000 170 Std Residual -2.198 3.242 0.000 0.982 170 a Dependent Variable: SD xxv xxvi xxvii Phụ lục 8: Phân tích Spearman Correlations ABSRES XH HQ DK RR DM Spearman's ABSRES Correlation 1.000 0.163* 0.102 -0.031 0.006 0.147 rho Coefficient Sig (20.033 0.187 0.691 0.940 0.055 tailed) N 170 170 170 170 170 170 XH Correlation 0.163* 1.000 0.196* 0.314** -0.170* 0.240** Coefficient Sig (20.033 0.010 0.000 0.027 002 tailed) N 170 170 170 170 170 170 HQ Correlation 0.102 0.196* 1.000 0.173* -0.084 0.255** Coefficient Sig (20.187 0.010 0.024 0.275 0.001 tailed) N 170 170 170 170 170 170 DK Correlation -0.031 0.314** 0.173* 1.000 -0.247** 0.138 Coefficient Sig (20.691 0.000 0.024 0.001 0.074 tailed) N 170 170 170 170 170 170 RR Correlation 0.006 -0.170* -0.084 -0.247** 1.000 -0.167* Coefficient Sig (20.940 0.027 0.275 0.001 0.030 tailed) N 170 170 170 170 170 170 DM Correlation 0.147 0.240** 0.255** 0.138 -0.167* 1.000 Coefficient Sig (20.055 0.002 0.001 0.074 0.030 tailed) N 170 170 170 170 170 170 * Correlation is significant at the 0.05 level (2-tailed) ** Correlation is significant at the 0.01 level (2-tailed) xxviii Phụ lục 9: Kiểm định khác biệt trung bình Phụ lục 9.1 Kiểm định khác biệt trung bình Theo giới tính Group Statistics Gioi_tinh SD Nu Nam N Mean Std Deviation Std Error Mean 100 3.3180 75590 07559 70 80021 09564 3.1714 Independent Samples Test Levene's Test for Equality of Variances F SD Equal variances assumed Equal variances not assumed Sig 0.005 0.943 t-test for Equality of Means t 1.215 Sig (2tailed) df 168 1.202 143.184 Mean Difference Std Error Difference 95% Confidence Interval of the Difference Lower Upper 0.226 0.14657 0.12068 -.09168 38482 0.231 0.14657 0.12191 -.09440 38754 Phụ lục 9.2 Kiểm định khác biệt trung bình Theo độ tuổi Descriptives SD Mean Std Deviation 16 3.2750 0.67676 0.16919 2.9144 3.6356 2.40 5.00 32 3.4375 0.76274 0.13483 3.1625 3.7125 2.00 5.00 92 3.2630 0.79445 0.08283 3.0985 3.4276 2.00 5.00 30 3.0400 0.76185 0.13909 2.7555 3.3245 2.00 5.00 N Duoi 20 tuoi Tu 20 tuoi den 30 tuoi Tu 30 tuoi den 40 tuoi Tu 40 Std Error 95% Confidence Interval for Mean Lower Upper Bound Bound Minimum Maximum xxix tuoi den 50 tuoi Total 17 3.2576 0.77549 0.05948 3.1402 3.3751 2.00 5.00 Test of Homogeneity of Variances Sudung Levene Statistic df1 df2 Sig 0.269 166 0.848 ANOVA SD Sum of Squares df Mean Square F Sig Between Groups 2.464 0.821 1.375 0.252 Within Groups 99.171 166 0.597 Total 101.635 169 Phụ lục 9.3 Kiểm định khác biệt trung bình Theo mức thu nhập Descriptives SD Duoi trieu Tu – 10 trieu Tu 10 – 20 trieu Trên 20 trieu Tôi chua 95% Confidence Interval for Mean Std Std Lower Upper N Mean Deviation Error Bound Bound Minimum Maximum 15 3.3333 0.45145 0.11656 3.0833 3.5833 2.60 4.00 92 3.2543 0.80717 0.08415 3.0872 3.4215 2.00 5.00 42 3.3143 0.74591 0.11510 3.0818 3.5467 2.00 5.00 3.2222 0.95102 0.31701 2.4912 3.9532 2.00 4.60 12 3.0167 0.87991 0.25401 2.4576 3.5757 2.00 5.00 xxx có thu nhap Total 170 3.2576 0.77549 0.05948 3.1402 3.3751 2.00 5.00 Test of Homogeneity of Variances SD Levene Statistic df1 df2 Sig 1.239 165 0.296 ANOVA SD Between Groups Within Groups Total Sum of Squares 930 100.705 101.635 Mean df Square 0.232 165 0.610 169 F 0.381 Sig 0.822 Phụ lục 9.4 Kiểm định khác biệt trung bình theo Nơi sinh sống Group Statistics Noi_sinh_song SD Vùng nông thôn Vùng thành thi 78 Mean 3.3410 Std Deviation 0.73581 92 3.1870 0.80482 N Std Error Mean 0.08331 0.08391 xxxi Independent Samples Test Levene's Test for Equality of Variances F SD Equal variances assumed Equal variances not assumed Sig t-test for Equality of Means t 0.244 0.622 1.293 1.303 df Sig (2taile d) Mean Differe nce Std Error Differe nce 95% Confidence Interval of the Difference Lower Upper 168 0.198 0.15407 0.11912 -0.08110 0.38924 167.023 0.194 0.15407 0.11824 -0.07938 0.38752 Available online at www.rajournals.in International Journal of Management and Economics Invention ISSN: 2395-7220 DOI: 10.47191/ijmei/v8i5.01 Volume: 08 Issue: 05 May 2022 International Open Access Impact Factor: 7.193 (SJIF) Page no.-2418-2423 Differences in Consumers' Intention to Use E-Payments in Large Cities and Small Provinces in Vietnam Nguyen Thi Thanh Van1, Bui Thi My Tien2 HCMC University of Technology and Education, Ho Chi Minh city, Vietnam TayNinh College of Economy and Technique, Tay Ninh province, Vietnam ARTICLE INFO ABSTRACT Published Online: 05 May 2022 The main objective of this paper was to contribute to the general understanding of consumer intention for using E-payment In particular, the study examines differences in consumer intention in large cities and small provinces A total 170 customers in Tay Ninh province and 131 customers in Ho Chi Minh city participated in this study by responding to a structured questionnaire The findings indicate that factors impacting consumer intention to use E-payment in big cities are effort expectancy, performance expectancy, social influence, user innovativeness, facilitating conditions Corresponding Author: However, there is a slight difference that effort expectancy does not affect consumer intention to Nguyen Thi Thanh use E-payment in Tay Ninh province, instead it is the perceived risk factor Therefore, E-payment service providers implement their development strategies Van KEYWORDS: E-payment, consumers' intention, UTAUT, Vietnam I INTRODUCTION E-payments are an important component of E-commerce As E-commerce grows, more and more E-payments will be made According to Euromonitor (a market research firm) data in March 2020 in Vietnam, the E-commerce value in 2019 reached USD 11.8 billion, a growth rate of 18% The annual growth rate is expected to be 16% and reach USD 26.1 billion by 2024 About E-payment, according to information from NAPAS (Vietnam National Payment Joint Stock Company), up to March 2020, the number of online payment transactions was about 76%, the total transaction value increased by 124% over the same period in 2019 In the first months of 2021, more than 800 million transactions were processed (equivalent to around VND million billion), an increase of 113% in quantity and a 169% increase in transaction value compared to the same period last year In Vietnam, E-payment is a new method made through mobile devices with network connection, suitable for the flow of the market such as payment via e-wallets Zalo pay, Momo, etc.; or direct payment from an electronic bank such as online payment internet banking; payment on smart phone - mobile banking; scanning visa card, master card, QR code These online payment methods are becoming more and more popular with many people because of their convenience, speed and ease The Covid-19 pandemic makes E-payment forms develop more than ever 2418 Customers using E-payment in Vietnam are often concentrated in big cities, who like convenience, speed and can experience trendy online services They are becoming familiar with this type of online payment However, in small provinces, this type of online transaction and electronic payment is not popular and still unfamiliar to consumers Therefore, this paper aims to contribute to the general understanding of consumer’s intention for using E-payment In particular, the study examines differences in consumer intention in large cities and small provinces II LITERATURE REVIEW E-payment E-payment payments are defined as payments made in electronic commerce environment in the form of money exchange through electronic means (Kaur & Pathak, 2015) Kabir, et al (2015) defined E-payment system as a collection of components and processes that enables two or more parties to transact and exchange monetary value via electronic means In Vietnam, from 2015 until now, E-payment has developed strongly alongside the development of the Internet, smartphones, bank cards and E-commerce sites Nowadays, in Vietnam, there are 04 most widely used Epayment channels, including: payment by card, payment by payment gateway, payment by e-wallet, and payment by smartphone Nguyen Thi Thanh Van1, IJMEI Volume 08 Issue 05 May 2022 “Differences in Consumers' Intention to Use E-Payments in Large Cities and Small Provinces in Vietnam” Technology Acceptance Model – TAM Davis et al (1989) provided Technology Acceptance Model - TAM to explain consumer acceptance behavior in the most fundamental and reasonable way Through studying people who use technology, TAM has surveyed external variables to internal perception, attitude, and intention The model includes: External variables, perceived usefulness, perceived ease of use, attitude towards using, behavioral intentions to use and actual system use Figure 1: Technology Acceptance Model - TAM Source: Davis et al (1989) Unified Theory of Acceptance and Use of Technology - UTAUT Venkatesh, et al (2003) developed the Unified Theory of Acceptance and Use of Technology - UTAUT through synthesizing and unifying Theory of Reasoned Action TRA, the Technology Acceptance Model TAM, Motivational Models MM, Theory of Planned Behavior TPB, the Model of the PC Utilization MPCU, Diffusion of Innovations theory DOI, and Social Cognitive Theory SCT The Unified Theory of Acceptance and Use of Technology - UTAUT has factors that affect intention and technology use: Performance Expectancy, Effort Expectancy, Social Influence, and Facilitating Conditions Figure 2: Unified Theory of Acceptance and Use of Technology - UTAUT Source: Venkatesh et al (2003) Performance expectancy is defined as the degree to which an individual believes that using the system will help him or her attain gains in job performance Performance expectancy is connected with these five concepts: perceived usefulness (TAM/TAM2 and C-TAM-TPB), extrinsic 2419 motivation (MM), job-fit (MPCU), relative advantage (IDT), and outcome expectations (SCT) Effort expectancy is defined as the degree of ease associated with the use of the system Effort expectancy is related to three concepts: perceived ease of use (TAM/TAM2), complexity (MPCU), and ease of use (IDT) Social influence is defined as the degree to which an individual perceives that important others believe he or she should use the new system Social influence is associated with three concepts: subjective norm (TRA, TAM2, TPB/IDTPB, and C-TAM-TPB), social factors (MPCU), and image (IDT) Facilitating conditions are defined as the degree to which an individual believes that an organizational and technical infrastructure exists to support use of the system Facilitating conditions are linked with three concepts: perceived behavioral control (TPBI DTPB, C-TAM-TPB), facilitating conditions (MPCU), and compatibility (IDT) Hypotheses Development for the Proposed Model Social influence: According to Junadi and Sfenrianto (2015), social influence will impact everyone around When relatives and friends use E-payment, the mentality of keeping up with modern trends will promote a far-reaching impact in society Relatives and friends are reliable sources of information for an individual to get introduced and familiarized with new trends because they have first-hand experience to consult and explain in a comprehensible and detailed manner Therefore, the study puts forward a hypothesis: H1: Social influence has positive impact on Consumers' intention to use E-payment Effort expectancy: According to the model of Junadi and Sfenrianto (2015) and Venkatesh, et al (2012), effort expectancy will increase the use of E-payment This model suggests that transactions on the internet are /should be easy to use with a few guided steps; a quick performance also provides simple and clear E-payment interactions This is the foundation for hypothesis: H2: Effort expectancy has positive impact on Consumers' intention to use E-payment Performance expectancy: Junadi and Sfenrianto (2015), Venkatesh, et al (2012) also give the result: E-payment helps boost transaction efficiency, and allows us to omit the tedious cash preparation step thus making transactions more convenient and faster On the other hand, Venkatesh, et al (2012) believe E-payment is very useful in everyday life Hence the suggestion of this hypothesis: H3: Performance expectancy has positive impact on Consumers' intention to use E-payment Facilitating conditions: With reference to the model of Venkatesh, et al (2003), given favorable conditions such as a readily available computer system with internet connection, it is easier and more likely to perform Epayment Besides, knowing how to use E-payment and getting updated on necessary information will promote this Nguyen Thi Thanh Van1, IJMEI Volume 08 Issue 05 May 2022 “Differences in Consumers' Intention to Use E-Payments in Large Cities and Small Provinces in Vietnam” behavior Furthermore, receiving external help from an instructor/an E-payment service provider will provide positive conditions for E-payment Lastly, with assistance from relatives, an individual will have an optimal guide to complete E-payment Therefore, this hypothesis is proposed: H4: Facilitating conditions has positive impact on Consumers' intention to use E-payment Perceived risk: According to Nguyễn Duy Thanh and Huỳnh Anh Phúc (2018); Lê Văn Phúc, et al (2019), even though consumers use E-payment, they are still worried about the risk level Consumers have a perception of this risk, and they suspect the money may get stolen or cheated in online internet transactions Furthermore, consumers fear for personal information leakage or data theft from hackers, or they fear that E-payment is not safe Therefore, the larger the risk is, the less likely a consumer accepts E-payment Hence the proposal of the hypothesis: H5: Perceived risk has negative impact on Consumers' intention to use E-payment User innovativeness: Referring to the model of Zhang & Kizildag (2018); Hirunyawipada and Paswan (2006); Lê Văn Phúc, et al (2019), it was shown that the more developed the information technology is, the more products are created Consumers always want to experience and discover new things and sometimes they want themselves to be the first to use a new product with a very proud attitude It is the same for E-payment, alongside the development of science and technology are many new channels of Epayment, more advanced, better in quality, faster than their predecessors Therefore, this hypothesis is proposed: H6: User innovativeness has positive impact on Consumers' intention to use E-payment III RESEARCH METHODOLOGY Measurement scale for the observed variables is inherited and modified from the scale of Junadi and Sfenrianto (2015), Venkatesh et al (2012) … and uses the 5point Likert scale where point means totally disagree and point means totally agree The research methodology is quantitative and the primary data is collected through surveys The sampling method adopted is convenience sampling Bollen (1989) suggested that an empirical ratio of at least five observations per each estimated parameter (5:1) Thus, a sample size of 100 (20x5) or more can be accepted for this research The surveyed people are consumers who have known about E-payment The survey is conducted in Ho Chi Minh city and Tay Ninh province There are 131 valid questionnaires at Ho Chi Minh city and 170 ones at Tay Ninh province with completed information used in the analysis IV THE RESULTS 4.1 Testing for Reliability of Scales The Cronbach’s Alpha in Table shows that all scales are rather hight (the minimum is 0.761>0.6) In the data from Tay Ninh province, HQ4 and DK4 items are removed and the item-total correlations of other items are over 0.3 Thus, all measurement items should be tested using Exploratory Factor Analysis (EFA) Table 1: Cronbach’s Alpha Results of Measurement Items Code Items Source XH1 XH2 XH3 NL1 NL2 NL3 HQ1 HQ2 HQ3 HQ4 2420 Social influence (XH) The important people (family/ relatives/ friends) recommends E-payment The important people (family/ relatives/ friends) use E-payment system The important people (family/ relatives/ friends) support the use of E-payment Effort expectancy (NL) Easy of use e-payment system Easy to learn E-payment system My interaction with E-payment is clear and understandable Performance expectancy (HQ) Productivity in the transaction Convenient in the transaction Speed in the transaction I find E-payment useful in my daily life Facilitating conditions (DK) Junadi Sfenrianto (2015) Cronbach’s Alpha Data from HCM City and 0.798 0.538 Data from Tay Ninh province 0.885 0.801 0.633 0.769 0.770 0.756 Junadi and Sfenrianto (2015) Venkatesh et al (2012) 0.793 0.545 0.749 0.623 0.887 0.734 0.789 Junadi and Sfenrianto (2015); Venkatesh et al (2012) 0.776 0.533 0.647 0.515 0.668 0.761 0.834 0.727 0.710 0.656 (removed) 0.883 Venkatesh et al 0.819 Nguyen Thi Thanh Van1, IJMEI Volume 08 Issue 05 May 2022 “Differences in Consumers' Intention to Use E-Payments in Large Cities and Small Provinces in Vietnam” DK1 DK2 DK3 DK4 RR1 RR2 RR3 RR4 DM1 DM2 DM3 SD1 SD2 SD3 SD4 SD5 I have the resources necessary to use Epayment I have the knowledge necessary to use Epayment E-payment is compatible with other technologies I can get help from others when I have difficulties using E-payment Perceived risk (RR) There may be leaked information online transactions There may be caused fraud or lost money when using E–payments There may be accessed into unauthorized personal data by hackers E–payment transactions may not be secure User innovativeness (DM) When I hear about a new product, I look for ways to try it Among my peers, I am usually the first one to try a new product Whenever the new product gets to the market, I am among the first to know Consumers' intention to use Epayment (SD) I plan to use E-payment I intend to using E-payment I intend to continue using E-payment in the future I plan to continue to use E-payment Recommend others to use e-payment system (2012) 0.604 0.814 0.603 0.748 0.561 Nguyen and Huynh (2018) 0.763 0.477 (removed) 0.832 0.655 0.829 0.667 0.655 0.664 0.652 Zhang and Kizildag (2018); Le et al (2019) 0.637 0.683 0.868 0.684 0.659 0.772 0.554 0.801 0.635 0.762 Junadi and Sfenrianto (2015) Venkatesh et al (2012); Phan et al (2020) Exploratory Factor Analysis (EFA) with principal axis factoring in conjunction with promax rotation was 0.672 0.817 0.895 0.531 0.450 0.699 0.707 0.763 0.735 0.654 0.793 0.675 0.770 conducted to explore dimensionality of factors (construct) The results shown in Table Table 2: Exploratory Factor Analysis (EFA) Results of Measurement Items Factor Social influence Effort expectancy Performance expectancy Facilitating conditions Perceived risk User innovativeness Consumers' intention to use E-payment 2421 Data from HCM City KMO Number Eigen-value of Items 0.739 0.777 3 1.032 Total variance explained 72.122 Data from Tay Ninh province KMO Number Eigenof Items value 0.753 3 3 5 2.934 58.684 0.885 1.43 Total variance explained 76.30 3.52 70,45 Nguyen Thi Thanh Van1, IJMEI Volume 08 Issue 05 May 2022 “Differences in Consumers' Intention to Use E-Payments in Large Cities and Small Provinces in Vietnam” With results of CRA and EFA, the scales of concepts are accepted and have their reliability guaranteed The number of factors extracted for factors that influence Consumers’ intention to use E-payment is 6, which is consistent with the proposed hypothesis 4.2 Results of hypotheses test Table 3: Results of Measurement Items Hypothesis Social influence Effort expectancy Performance expectancy Facilitating conditions Perceived risk User innovativeness H1 H2 H3 H4 H5 H6 Data from HCM City Standardized Sig Coefficients 0.402 0.000 0.182 0.007 0.311 0.000 0.234 0.001 -0.021 0.756 0.320 0.000 From table 3, a difference is shown between E-payment users in Ho Chi Minh City and Tay Ninh province In Ho Chi Minh city, H5 examines the relationship between perceived risk and consumers’ intention to use E-payment, which is not supported with p-value = 0.756 > 0.05 In Tay Ninh province, Effort expectancy was also found not to have a positive impact on Consumers' intention to use E-payment – H2 is not supported with p-value = 0.080 > 0.05 Besides, all the remaining hypotheses are supported as proposed by the model V CONCLUSION AND IMPLICATIONS The study is based on theories of TAM, UTAUT and previous studies to examine factors that affect consumer intention of E-payment In particular, the study examines differences in consumer intention in large cities and small provinces The result shows that Ho Chi Minh city and Tay Ninh province both have the factors affecting consumer intention to use E-payment: Social influence, Performance expectancy, Facilitating conditions, User innovativeness However, there are differences between consumer intention to use E-payment in Ho Chi Minh city and Tay Ninh province In Ho Chi Minh city, Effort expectancy has a positive impact on the intention to use E-payment while Perceived risk does not In Tay Ninh province, this trend is reversed: Perceived risk has a positive impact on the intention to use E-payment while Effort expectancy does not This result is necessary for E-payment service providers to expand their user network Factor “Social influence” From this factor, the fact that friends or relatives currently use E-payment is an important factor to encourage another new user to use E-payment Influence from acquaintances is an iconic cultural feature of Vietnam Epayment service providers can attract relatives of existing consumers through offers and promotions for themselves and their relatives Factor “Performance expectancy” 2422 Hypothesis support Yes Yes Yes Yes No Yes Data from Tay Ninh province Standardized Sig Hypothesis Coefficients support 0.256 0.000 Yes 0.094 0.080 No 0.253 0.000 Yes 0.321 0.000 Yes -0.179 0.002 Yes 0.151 0.008 Yes E-payment services should have programs to demonstrate the effectiveness of E-payment methods, allowing every consumer to understand and experience using E-payment methods, thus letting them realize in the most transparent and specific way how simpler, faster and more convenient E-payment is than using cash Factor “Facilitating conditions” Companies that provide E-payment service should standardize the process of E-payment in detail so that the consumers can easily follow In addition, companies should augment activities and provide consulting services to guide users to effortlessly perform E-payment The higher these support conditions, the easier and more likely for the user to perform E-payment Factor “User innovativeness” Companies that provide E-payment service should frequently research, update new features, interfaces They should actively promote to ensure that users access information about new and improved aspects thus convincing them into using this new payment method They should cooperate with partner companies and banks to upgrade new infrastructure of the E-payment system, thus always providing new, advanced services, products that satisfy the growing demand of the consumers Factor “Perceived risk” For Tay Ninh consumers, this factor impacts on intention to use E-payment According to survey data, consumers are concerned about personal information leakage, the toll of the transaction, data theft from hackers, or unsafe payment Companies that provide E-payment services need to upgrade infrastructure and improve security Financial institutions, banks, fintechs, and telecommunications businesses need to cooperate to establish an interconnected payment network that is convenient and safe for consumers In addition, they should regularly update, forewarn consumers about fraudulent forms of E-payment Factor “Effort expectancy” measures the level of ease of use associated with the use of an information technology Nguyen Thi Thanh Van1, IJMEI Volume 08 Issue 05 May 2022 “Differences in Consumers' Intention to Use E-Payments in Large Cities and Small Provinces in Vietnam” For Ho Chi Minh city consumers, this factor impacts on intention to use E-payment Therefore, companies that provide E-payment service need to improve the service’s ease of use, simple and convenient app, suitable for consumers from different ages and levels of tech-savviness The interface of the app needs to be intuitively simple to minimize payment time 11 Zhang, T., Lu, C and Kizildag, M (2018) Banking “on-the-go”: examining consumers’ adoption of mobile banking services International Journal of Quality and Service Sciences.10:279-295 ACKNOWLEDGEMENT This work belongs to the project grant No: T2021-21 funded by Ho chi Minh city university of Technology and Education, Vietnam REFERENCES Bollen, K A (1989) Structural Equations with Latent Variables John Wiley & Son, Inc Davis, F D., Bagozzi, R P., & Warshaw, P R (1989) User acceptance of computer technology: a comparison of two theoretical models Management science, 35(8):982-1003 Junadi, S (2015) A Model of Factors Influencing Consumer’s Intention To Use E-Payment System in Indonesia, Procedia Computer Science, 59:214-220 Hirunyawipada, T and Paswan, A.K (2006) Consumer innovativeness and perceived risk: implications for high technology product adoption Journal of Consumer Marketing, 23:182-198 Kabir, M.A, Saidin, S.Z and Ahmi, A (2015) Adoption of e-Payment Systems: A Review of Literature Proceedings of the International Conference on E-Commerce Kaur, K., & Pathak, A (2015) E-Payment System on E-Commerce in India Karamjeet Kaur International Journal of Engineering Research and Applications, 5(2):79-87 Le, V.P, Nguyen, H.N.L and Dang, Q.T (2019) Factors affecting the intention to use fintech services in Vietnam Economics, Management And Business (Ciemb 2019), 275-295 Nguyen, D.T and Huynh, A.P (2017) Chất lượng dịch vụ ảnh hưởng xã hội chấp nhận tốn điện tử, Tạp chí Phát triển Khoa học Công nghệ, 20:72-80 Phan, H.N., Tran, M.D., Hoang, V.H and Dang, T.D 2020 Determinants influencing customers' decision to use mobile payment services: The case of Vietnam Management Science Letters, 10:26352646 10 Venkatesh, V., Thong, J.Y.L., Xu, X (2012) Consumer acceptance and use of information technology: extending the unified theory of acceptance and use of technology MIS Quarterly, 36:157-178 2423 Nguyen Thi Thanh Van1, IJMEI Volume 08 Issue 05 May 2022 S K L 0 ... Mục tiêu chung: Đề tài nghiên cứu yếu tố tác động đến ý định sử dụng toán điện tử người tiêu dùng Tây Ninh Mục tiêu cụ thể: Xác định yếu tố ảnh hưởng đến việc ý định sử dụng toán điện tử người tiêu. .. yếu tố tác động đến việc ý định sử dụng toán điện tử người tiêu dùng Tây Ninh? ?? cần thiết Từ đề xuất hàm ý kiến nghị để gia tăng sử dụng toán điện tử cho người tiêu dùng Tây Ninh 1.2 Mục tiêu. .. hoạch để sử dụng tốn điện tử SD2 Tơi có ý định sử dụng tốn điện tử SD3 Tơi có ý định tiếp tục sử dụng toán điện tử dụng tốn tương lai SD4 điện tử Tơi có ý định sử dụng toán điện tử thường xuyên