LIST OF ABBREVIATIONSCharacters Full nameAI Artificial Intelligence C-TAM-TPB Combined TAM - TPB DNSE DNSE Securities Joint Stock Company DOI The Diffusion of Innovation Theory EE Effort
INTRODUCTION SG 2+ S11 1T HH HH HH như 1
Research Background 0 Aa5-
Stock investment Stock investing refers to the act of purchasing shares of a publicly traded company with the expectation of generating profits as the stock value increases over time or from receiving dividends paid by the company Stock investments are often made by individuals, institutional investors and investment funds with the goal of achieving short- term or long-term profits Stock investment performance depends on many factors, including company financial performance, general market conditions and investor sentiment Effective stock investing requires a thorough understanding of the financial markets and analysis of relevant economic, financial and industry data.
Stock investment is an effective investment channel in difficult economic times like today and analyzing securities for investment is very important in attracting customers to invest The analysis will include many factors: macro-environment assessment, industry assessment, stock market assessment, company analysis, etc., along with individual securities to determine investment efficiency can be obtained commensurate with the expected level of risk.
Feature AI Broker in EntradeX stock trading platform Artificial intelligence (AI) describes the ability of computers and programming software to perform tasks related to human cognition, reasoning, learning, and making choices and decisions AI describes the process or development of computer systems and algorithms that can simulate and augment human intelligence in a variety of ways.
AI is a collection of many subfields such as processing and reception techniques natural language, computer vision, robotics and expert systems, among many other fields These techniques enable machines to learn from data, reason, and make decisions based on complex algorithms and models.
AI has numerous applications in various domains, such as healthcare, finance,transportation, manufacturing, and entertainment, among others Examples of AI applications include image recognition, speech recognition, autonomous vehicles, personalized medicine, and chatbots, among others.
As AI technologies continue to develop, they have the opportunity to transform working and learning environments, bringing new opportunities and solutions to many of the world's most pressing challenges However, they also raise social and economic and ethical concerns such as the impact on work causing unemployment, privacy and personal judgment, among others.
Entrade X by DNSE is the basic stock trading application of DNSE Securities Joint Stock Company (DNSE), launched in 2021 on the smart device platform DNSE hopes to contribute to changing the way securities investors trade today The utilities on the application will help investors easily monitor the market, find opportunities and make transactions more effectively.
The Future AI Broker in the EntradeX trading platform is a tool to help investors understand information about the market, stocks and from there to make investment decisions This is a tool that provides fully automatic information based on analytical data on the Vietnamese stock market This feature includes 3 characteristics: The first is to provide information selectively to help investors understand the main information on the stock market, including macro information, industry information, stock information quickly and accurately The second is making investment recommendations based on analytical data and established algorithms Finally, personalization is based on investor characteristics to provide the most suitable investment options for each investor.
Entrade X is a mobile application founded by Dai Nam Joint Stock Company, launched in 2021 In addition to a simple and convenient trading experience, the application also allows investors to open an account completely online along with signing an electronic contract through an electronic customer identification (eK YC - Electronic Know) solution.
With an electronic customer identification (eK YC) solution, just a phone with an Internet connection, investors can open an account anytime, anywhere in just 3-5 minutes without having to come in person transaction counter Accordingly, the traditional account opening contract with the method of completing the hard copy company profile will be completely replaced by an electronic contract The application of technology to replace face-to-face meetings in procedures and processes has significantly shortened the time it takes for a customer to open an account, conduct transactions, and at the same time optimize business resources and enhance customer experience.
Open Entrade X account in DNSE Securities Company
To open a trading account at DNSE Securities Company, customers can use one of the following two ways:
Method 1: Go directly to the trading office of the securities company Remember to bring a valid ID card or citizen identification card to complete the procedure.
Method 2: Open an online account right at home.
As for how to open an online account, you can choose one of the following two ways:
Method 1: Open an account via website: dnse.com.vn Step 1: Access the website at dnse.com.vn
& DNSE Thitrudngy Hocdautuy Sản phẩm+ Hỗ trợ Về DNSE~ Đăng nhập [ Mởuikhon ệ
Step 3: Complete the registration information according to the available form
& DNSE Thị trường Hocdautu~ Sản phẩmx Hétrg~ Về DNSE Q Đăng nhập@
RA Entrade” He ¿ by DNSE
Step 4: Verify account information via email and phone number
Method 2: Open an account through the Entrade X trading platformlication on Appstore or CHPlay
Step 1: Download the Entrade X trading platformlication on iOS or Android
Figure 1.3: App Entrade X on Android
Step 2: Open the application and complete personal information
Kích hoạt tài khoản trước 19:39 29/03/2021 dé giữ số tài khoản
Chỉ cắn 1 phút đề thực hiện.
Figure 1.4: Form and certification to registration stock account
Step 4: Activate account via registration email.
Xác nhận số điện thoại
Vui lòng nhận mã OTP qửi đến số
Figure 1.5: Confirm OTP Feature AI Broker definition
With the desire to replace the work of traditional brokers, Entrade X is building an investment automation feature called AI Broker on an application platform, which is a tool to help investors gain information about the market markets, stocks and thereby make investment decisions.
All information is automated by the system and arranged with individuals in bringing information about the market and stocks to help investors save time in information selection, stock selection bonds or forms of investment quickly and accurately.
How to use the AI Broker feature Currently AI Broker includes 2 main information, the first is providing information to investors directly on the app, investors can go to the message section to select AI Broker, above will show information about market, about stocks.
Chúc mừng bạn đã được nhận
⁄ Kích hoạt Nộp tiền Đầu tư (5 triệu)
Trang chủ Theo dõi Theo dõi Sổ lệnh Sở hữu Tin nhan
Figure 1.6: AI broker on message in Entrade X trading platform
In addition, the investment idea feature also appears, investors click on the investment idea on the screen, a list of daily recommendations and investment arguments will appear.
10:01 | 19,2KB/s © Ý tưởng đầu tư đã được nhận
P/E: LN quy 17.3x +3, Định giá P/E hôm nay: 17.3x, đắt hơn P/E thị trường là 12.8x
Lợi nhuận sau thuế quý 2/2023: +3,227.51% so với cùng kỳ, tốt hơn +12.40%
Doanh thu quý 2/2023: +23.63% so với cùng kỳ, tốt hơn +20 6
Figure 1.7: Suggest investment of AI Broker Second is direct interaction, currently this product is only for interested and registered customers to be able to conveniently talk and ask the AI questions related to the information investors want.
Giới thiệu công tyNKG 2.=o py w
Công ty Cố phần Thép Nam Kim (NKG) được thành lập vào năm
2002 với vốn điều lệ ban đầu là 60 tỷ đồng Công ty hoạt động trong lĩnh vực sản xuất thép và có trụ sở chính tại Bình Dương Hoạt động sản xuất chính của NKG là san xuất các loại tôn thép như tôn mạ kẽm, tôn mạ màu và kinh doanh sắt thép các loại Hiện tại, NKG quản lý và vận hành 04 nhà máy với tống công suất sản xuất là 1,2 triệu tấn sản phẩm mạ cuối cùng mỗi năm NKG là doanh nghiệp. thép duy nhất ở Việt Nam san xuất được tôn mạ kẽm Z600 độ day 3mm Cng ty đã niêm yết trên sàn HOSE từ ngày 14/01/2011 và có số lượng cố phiếu đang lưu hành là 263,277,806 cố phiếu Tống tài leo sản của công ty là 12,178,966.349,173 đồng và vốn hoá là b
PS 5.397.195,023,000 đồng Đế biết thêm thông tin chỉ tiết, bạn có thế |
@ truy cập vào trang web của công ty tại tonnamkim.com ?
Research Scope
Intention to use Future AI Broker in EntradeX stock trading platform in investing in securities of individual customers and factors affecting intention to use Future AI Broker in EntradeX stock trading platform in securities investment In this thesis, the use of the feature is implied as the act of reading the notice and using the recommendation in the process invest.
In this study, the author focuses on studying the factors affecting the intention to use the Future AI Broker in the Entrade X stock trading platform.
Spatial scope: implemented on all individuals using the Entrade X stock trading platform, who has total investment asset of more than 1 billion VND this application and are between the ages of 20-50 years old.
Time range: the study was carried out from March 2023 to June 2023.
Research Structure - - - 5 111 HH TH TH HH HH Hư 12
This thesis is divided into five chapters, as presented as follow:
Chapter 1: Introduction Chapter 1 showed out the need to research factors that influence the intention to use the AI Broker feature in Entrade X trading platform, including evaluating the potential and benefits of research for the company The author also points out research models as a basis for building the foundation for the research model in this thesis In chapter 1, the author also clarifies the, research objectives, research questions and scope.
Chapter 2: Literature review Based on the research on the intention to accept and use a feature in chapter 1, the author has studied, an overview of the intention to accept in the customer's behavior These studies have developed based on the original theoretical model and added to it the factors affecting the intention to accept and use new features as Technology acceptance model-TAM, acceptance and use model Unified technology
UTAUT, The Innovation Diffusion Theory (IDT) and The Theory of Planned Behavior (TPB) On that basis, the author will synthesize, analyze and evaluate the factors affecting the intention to use the feature and build a scale for these factors.
Chapter 3: Research Design and Methodology This chapter presented the research process, including qualitative research on how to build the scale, and conduct hand-to-hand discussions Qualitative research results help build a formal research model and build a scale in quantitative research.
By combining both qualitative and quantitative research methods Information about usage time, frequency of use of features, attractive factors will be collected on the app In addition, the author will interview and survey on the EntradeX app and paper survey, customers who use the EntradeX securities app between the ages of 20-50 and have total investment assets of VND 1 billion or more (estimated), about more than 300 customer All information will be measured and collected during March and June 2023.
Chapter 4: Research Result Presenting and interpreting research results, describing survey samples, testing Cronbach's Alpha reliability, exploratory factor analysis (EFA), regression model measuring factors affecting intention to use AI features Broker on the Entrade X stock trading platform.
Chapter 5: Conclusion and Suggestions This chapter answers the research questions, discuss research findings as well as giving some suggestions or any solutions to the found results, limitations and further research direction
LITERATURE REIVIEW - SG HS SH HH HH HH Hư, 14 2.1 Literature review on research model . -s + + x+sx*sEsvEeeEeeeesessessers 14
Some research related to the use of stock exchange applications
Table 2.2: Some research related to the use of stock exchange applications
Author Theoretical model Platform model Factors affecting behavioral intention Cho, H., & Kim, Y.
Factors affecting the intention to use mobile stock trading apps: Empirical evidence from individual investors in Korea
Perceived ease of use, perceived usefulness, service quality, reliability of the app, and interactivity with users
Factors influencing the adoption of mobile stock trading: Evidence
Perceived ease of use, perceived usefulness, service quality, reliability
23 from the Chinese of the app, speed of securities market access, and user experience.
Lee, J Y., & Park, | Factors influencing | Technology Perceived
M 2016 the adoption of | Acceptance Model | usefulness, mobile stock trading (TAM) perceived ease of applications: use, user Evidence from experience, and
Korea reliability of the app.
Lu, J.C., & Su, C | Factors affecting | Technology Perceived
H intention to use | Acceptance Model | usefulness, mobile stock trading applications:
Empirical evidence from individual investors in Taiwan
(TAM) perceived ease of use, enjoyment, and trust.
Determinants continued use mobile stock trading apps: Evidence from Pakistan
Unified Theory of Acceptance and Use of Technology (UTAUT)
Perceived ease of use, perceived usefulness, user experience, reliability of the app, expected consequences, and confirmation of expectations.
Proposed research MOdel - + + +31 332183 1189 11 911118111 111 ng ng 25
On the basis of the presented theory as well as studies on e-wallets using the acceptance theory model and using the UTAUT-2 extension fusion technology, the author proposes a model below are the hypotheses used for the research model:
Performance Expectancy (PE): can be defined as the degree to which users expect that using the system will help achieve job performance Being more specific means users are more likely to use new technology when they think it will help them do their jobs For Future Ai broker in Entrade X trading platform, Performance Expectancy is defined as the extent to which Feature AI Broker in Entrade stock market research.
HI: Performance expectancy(PE): has a positive (+) effect on intention to use Future AI Broker in EntradeX stock trading platform.
Effort Expectancy (EE): the second concept, can be defined as the degree of ease associated with using the system For the Future AI Broker in the Entrade X stock trading platform, Effort Expectancy is defined as the ease with which it is involved in using the Future AI Broker in the Entrade X stock trading platform.
H2: Effort Expectancy (EE): has a positive (+) effect on intention to use Future
AI Broker in Entrade X stock trading platform.
Social Influence (ST): is an individual's perception that significant others think and recommend that they use the new system For the AI Futures Broker in the Entrade X stock trading platform, social influence is the degree to which relevant members, such as family, friends, influence another's behavior when use this feature.
AI Broker in Entrade X stock trading platform.
H3: Social influence (SI): has a positive effect (+) on intention to use Future
AI Broker in Entrade X stock trading platform.
Facilitating Conditions (FC): the degree to which an individual believes there is a good technical and organizational infrastructure to support the use of the system. For the Future AI Broker in the Entrade Xb stock trading platform, favorable conditions are smartphones, domestic bank cards with functions such as online
25 banking (Internet Banking), online payment (E) -Commerce), auto-trading, auto- provisioning
H4: Favorable conditions (FC): has a positive (+) effect on intention to use Future AI Broker in Entrade X stock trading platform.
Hedonic Motivation (HM): is explained as the pleasure that comes from using technology For the Future AI Broker in the Entrade X stock trading platform, motivation is defined as the level of joy or pleasure that comes from using future AI Broker in Entrade X trading platform such as investment efficiency is improved.
HS: Hedonic motivation (HM): has a positive (+) effect on the intention to use Future AI Broker in the Entrade X stock trading platform.
Price Value(PV): Value is the customer's intention to use when the benefits of using technology have a positive impact on the customer's mindset in using it For the Future AI Broker in the Entrade X stock trading platform, perceived value is the incentives, costs or time that users can save.
H6: Perceived value (PV): has a positive (+) effect on intention to use Future
AI Broker in the Entrade X stock trading platform.
Habit (HT): is defined as the degree to which people tend to perform learned automatic behaviors For the Future AI Broker in the Entrade X stock trading platform. Habit is defined as the degree to which people tend to use the Future AI Broker in the Entrade X stock trading platform .
H7: Usage habit (HT): has a positive (+) effect on the intention to use Future
AI Broker in the Entrade X stock trading platform .
Inhering knowledge from previous studies, the author proposes a model with
7 expected useful factors, Effort Expectancy, social influence, favorable conditions, hedonic motivation, perceived value, habit familiar.
The modified UTAUT-—2 model of this study includes 7 independent variables,
1 anthropologically censored and 1 dependent variable.
~ Intention to use Favorable conditions
Figure 2.5: The proposed research model
RESEARCH DESIGN AND METHODOLOGY
Preliminary research (quaẽIfafIV€) - .- c1 v1 ng ng rệt 31
Subjects of the survey: Users who have used or intend to use the Future AI Broker in the Entrade X trading platformlication, selected randomly by gender and age, but ensuring that the investment account is at the level of over 1 billion VND.
Determining the sample size: This study includes 8 variables, of which 1 is dependent and 7 are independent Therefore, for exploratory factor analysis (EFA), the required sample size is 125 samples (N > 5*25 with 25 is the total number of observed variables) According to Tabachnick and Fidell (1996), the minimum optimal sample size for multiple regression analysis is as follows: N=8m+50 (Where N is the sample size, m is the number of independent variables in the model) For this study, the number of samples needed is N > 8*7+506 samples To ensure representativeness and reach the sample size, the author conducted a survey of 350 samples in the form of 80 paper questionnaires, and 270 samples through online surveys.
The author uses SPSS 20 software for data analysis and running results.
Descriptive statistics: Use statistical tools such as frequency and percentage Evaluate Cronbach's Alpha reliability coefficient
In this research, statistical significance is only accepted for scales with Cronbach's Alpha coefficient greater than 0.6 demonstrate a qualified measurement scale.
Exploratory factor analysis (EFA) The EFA exploratory factor testing method is mainly used to evaluate convergent validity and discriminant validity.
In EFA factor analysis, we need to pay attention to a number of criteria such as:
KMO index (Kalser-Meyer — Olkin measure of sampling adequacy): a large KMO value (0.5 < KMO < 1) is a sufficient condition for appropriate factor analysis.
Bartlett's test is statistically significant (Sig < 0.05): this is a statistical quantity used to consider the hypothesis that variables are not correlated in the population.
QUANTITATIVE RESEARCH AND RESEARCH RESULTS
Linear regression analySis - 6 133 vn HH HH ng nưệt 49
Model R RSquare | Adjusted | Std Error | Durbin-
1 726a 527 17 50776 1.950 a Predictors: (Constant), PE, EE, FC, SI, HM, TT, PV b Dependent Variable: IU
To evaluate the suitability of the model, we use the adjusted R2, the result of the adjusted R2 is 51.7% smaller than R2 52.7% The results demonstrate that this
49 linear regression model fits the sample data set at 52.7%, meaning that the independent variables explain 52.7% of the variation in intention to use Feature AI Broker in the background Entrade X trading platform.
The results of regression analysis show that the Sig of the factors Performance expectancy (PE), Effort Expectancy (EE), Social influence (SI), Favorable conditions (FC), Hedonic motivation (HM), Perceived value (PV) and Trust (TT) are less than 0.05, so it can be confirmed that these factors are meaningful in the model.
Check regression assumptions Assumption of linear association: checked by scatter plots for standardized residuals and standardized predicted values The obtained results show that the standardized residuals are distributed concentrated around the 0-intercept line, so the linear relationship assumption is not violated.
Regression Standardized Residual ho o o o ỉ Po O 2° 2 “2 le) of @ eo & fe 2 & @ le
Figure 4.1: Scatterplot of dependent variable IU
Assume there 1s no correlation between the residuals: the results show that the Durbin—Waston statistical quantity has a value of 1.905 in the range of 1—3, so the hypothesis of no autocorrelation is accepted.
Assume the residuals are normally distributed: The residual scatter plot shows that the residual distribution is approximately normal The mean value MEAN is close to = 0, the standard deviation Std = 0.990 is close to 1 Therefore, it can be concluded that: the normal distribution hypothesis of the residuals is not violated.
Figure 4.2: Histogram of dependent variable IU
Normal P-P Plot of Regression Standardized Residual
Figure 4.3: P-P Plot of regression Standardize Residual Plot chart shows the values of the percentile points of the distribution of - variables according to the percentiles of the normal distribution
Multicollinearity phenomenon: The results of testing the multicollinearity phenomenon as shown in table 4.8 show that the VIF coefficients of the independent variables in the model are all less than 2, so it proves that the phenomenon does not occur between the independent variables multicollinearity
Evaluate and check the fit of the model .- - ôse <+sÊ+scseessexss 52
Model Sum of df Mean F Sig.
Residual 88.174 342 258 Total 186.412 349 a Dependent Variable: IU b Predictors: (Constant), PP, EE, SI, FC, HM, PV, TT
The results obtained from the ANOVA table show that the F statistical value with a Sig value of less than 0.005 shows that it is safe to reject the Ho hypothesis that all regression coefficients are equal to 0 Therefore, we can concluded that the regression model satisfies the evaluation conditions and tests its suitability for drawing research results.
The results of regression analysis show that the Sig of the factors are all less than 0.05 and the Bk value is >0 so the Hypotheses FE, EE, SI, FC, HM, PV, TT are all accepted with a significance level of 0.000 as summarized:
HI Performance expectancy(PE): has a positive (+) | 0.00 Approve effect on intention to use Future AI Broker in Entrade X trading platform.
H2 Effort Expectancy (EE): has a positive (+) effect | 0.00 Approve on intention to use Future AI Broker in Entrade
H3 Social influence (SI): has a positive effect (+) on | 0.00 Approve intention to use Future AI Broker in Entrade X trading platform.
H4 Favorable conditions (FC): has a positive (+) | 0.00 Approve effect on intention to use Future AI Broker in Entrade X trading platform.
HS Hedonic motivation (HM): has a positive (+) | 0.00 Approve effect on intention to use Future AI Broker in Entrade X trading platform.
H6 There is a positive (+) effect on intention to use | 0.00 Approve
Future AI Broker in Entrade X trading platform.
H7 Trust (TT): has a positive (+) effect on intention | 0.00 Approve to use Future AI Broker in Entrade X trading platform.
IU = 0.406*PE + 0.243*EE + 0.246*SI + 0.200*FC + 0.206*HM + 0.193*PV + 0.158*TT
Based on the linear regression equation, the author finds the significance of the independent variables on the change in intention to use Future AI Broker in Entrade X trading platform as follows:
In case other factors remain unchanged, " Performance expectancy" increases by 1 unit, then the Intention to use Future AI Broker in Entrade X trading platform increases by 0.406 units (Standardized Coefficient Beta= 0.406).
In case other factors remain unchanged, "Effort expectancy" increases by 1 unit, then the Intention to use Future AI Broker in Entrade X trading platform application increases by 0.2434 units (Standardized Coefficient Beta = 0.243).
In case other factors remain unchanged, "Social influence" increases by 1 unit, then the Intention to use Future AI Broker in Entrade X trading platform increases by 0.246 units (Standardized Coefficient Beta = 0.246).
In case other factors remain unchanged, "Favorable conditions" increase by 1 unit, then the Intention to use Future AI Broker in Entrade X trading platform increases by 0.200 units (Standardized Coefficient Beta = 0.200).
In case other factors remain unchanged, "Hedonic motivation" increases by 1 unit, then the Intention to use Future AI Broker in Entrade X trading platform increases by 0.206 units (Standardized Coefficient Beta = 0.206).
In case other factors remain unchanged, "Perceived value" increases by 1 unit, then the Intention to use Future AI Broker in Entrade X trading platform increases by 0.193 units (Standardized Coefficient Beta = 0.193).
In case other factors remain unchanged, "Trust" increases by 1 unit, then the Intention to use Future AI Broker in Entrade X trading platform increases by 0.158 units (Standardized Coefficient Beta = 0.158).
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Levene test results (F test) Sig = 0.406 > 0.05, so the variances of the two populations are not different, we must use the t-test results in the line assuming equal variances (Equal variances not assumed).
Table 4.12: Independent Samples Test by Gender Levene’s t-test for Equality of Means test for equality of Variances
F | Sig t df Sig Mean Std Error 95%
(2- Difference | Difference Confidence tailed) Interval of the
Table 4.13: Group statistics by gender
Gender N Mean Std Std Error
HO: There is no difference in intention to use Feature AI Broker in Entrade X trading platform between age groups.
HI: There is a difference in intention to use use Feature AI Broker in Entrade
X trading platform between age groups.
Table 4.14: Anova Test by Age
Sum of df Mean F Sig.
Consider ANOVA test, sig = 0.000 < 0.05 HO should be rejected and H1 accepted There are differences in the intention to use Feature AI Broker in Entrade
X trading platform between age groups.
Table 4.15: Independent Samples Test by Age
(D Age (J) Age Mean Std Sig 95% Confidence
* The mean difference is significant at the 0.05 level.
Results of in-depth analysis of Post Hoc Test and sample mean values of each pair of two age groups, we see that the age groups from 22-34 years old, from 34-46 years old intend to use higher than the group under 22 years old, and over 46 years old In addition, there is no difference between the age groups under 22 and over 46.
HO: There is no difference in intention to use Feature AI Broker in Entrade X trading platform between occupation groups.
HI: There is a difference in intention to use use Feature AI Broker in Entrade
X trading platform between occupation groups.
Table 4.16: Anova Test by occupation
Sum of df Mean F Sig.
Consider ANOVA test, sig = 0.000 < 0.05 HO should be rejected and H1 accepted There are differences in the intention to use Feature AI Broker in Entrade
X trading platform between occupational groups.
Table 4.17: Independent Samples Test by occupation
(D Work | (J) Work Mean Std Sig 95% Confidence
* The mean difference is significant at the 0.05 level.
Results of in-depth analysis of Post Hoc Test and sample mean value, we see that managers and staff workers have higher intention to use than the student group, students and other occupational groups, in addition, between the staff occupational group, there is a difference in intention to use use Feature AI Broker in Entrade X trading platform compared to the student occupational group, students and the other occupational group different because sig is 0.000 < 0.05 respectively
HO: There is no difference in intention to use Feature AI Broker in Entrade X trading platform between education groups.
H1: There is a difference in intention to use use Feature AI Broker in Entrade
X trading platform between education groups.
Table 4.18: Anova Test by education
Sum of df Mean F Sig.
Consider ANOVA test, sig = 0.000 < 0.05 Ho should be rejected and HI accepted There are differences in the intention to use Feature AI Broker in Entrade
X trading platform between educational groups.
Table 4.19: Independent Samples Test by education (D Study | (J) Study Mean Std Sig 95% Confidence
* The mean difference is significant at the 0.05 level.
The results of in-depth analysis of the Post Hoc Test and the sample mean value of each pair of education, we see that university and master have the intention usage is higher than high school and other education groups In addition, there is a difference in intention to use Feature AI Broker in Entrade X trading platform
59 application between master, university with high school and other High school and other education groups have no difference in intention to use.
HO: There is no difference in intention to use Feature AI Broker in Entrade X trading platform between income groups.
HI: There is a difference in intention to use use Feature AI Broker in Entrade
X trading platform between income groups.
Table 4.20: Anova Test by income
Sum of df Mean F Sig.
Consider ANOVA test, sig = 0.000 < 0.05 Ho should be rejected and H1 accepted There are differences in the intention to use Feature AI Broker in Entrade
Table 4.21: Independent Samples Test by income (D (J) Mean Std Sig 95% Confidence Benefit | Benefit | Difference | Error Interval
* The mean difference is significant at the 0.05 level.
Results of in-depth analysis of Post Hoc Test and sample mean value of each income pair, we see that the group with income under 30 million VND has a lower mean value of intention to use than the group with income from 40-50 million and over million because sig is 0.000 < 0.05 From there, it can be concluded that the income group of 40-50 million and over 50 million higher intention to use future AIBroker in Entrade X trading platform.
Implications for business manag€Im€I + xxx seeseeesereersersee 61
Factors affecting the intention to use AI features on the Entrade x trading platform - a new technology - are important for businesses’ business management because they can help businesses identify factors elements need to be focused on promoting customer acceptance of new technology.
In an increasingly competitive and complex market context, the development and application of new technologies is an important factor to help businesses improve their competitiveness and achieve their business goals - especially for the stock market, which is already the playground of many large and long-standing companies. However, applying new technology also poses risks, such as high investment costs, difficulties in deployment and operation, and customers' fear of change.
Therefore, understanding the factors that influence the intention to use AI Feature on the Entrade X trading platform - a core and competitive product of the company will help businesses come up with appropriate measures to reduce Minimize risks and increase the chance of success in applying new technology.
Through research, it is likely that companies need to focus on developing new technologies that have real value for customers as shown through key efficiency factors This can be done through market research to determine customer needs and wants.
Businesses can ensure the ease of use of new technologies This can be done through the design and development of new technologies that are user-friendly, easy to understand, and easy to learn.
Businesses can build customer trust in new technologies This can be done through ensuring that new technologies operate stably, safely, and securely.
Businesses can influence customer perceptions of new technologies This can be done through marketing and communication activities.
Applying factors that affect the acceptance of new technology requires businesses to conduct careful research and analysis to choose measures appropriate to the characteristics of new technology and target customers targets, potential customers.
CONCLUSION AND SUGGESTIONS - s c2 cSccsecxe2 63 hNN®udl odỪD
Limitations and directions for further research - -ssc+<<<sx+scssr+ 77
This research only stops at studying the factors that affect the intention to use the AI Broker feature in Entrade customers, investors about the most popular features, the most useful things for customers Although there are many connections, from
77 customers' intention to use features to actual feature usage behavior, they are still influenced by many factors.
There are many different factors that can influence it such as changes in technology, fluctuations in the stock market, the economy, and individual preferences. This research only focuses on understanding the feelings of customers and investors about Performance expectancy, effort expectancy, Social influence, favorable condition, hedonic motivation, perceived value and trust to their intention to use the
AI Broker feature in Entrade X trading platform.
In addition, the factors affecting the intention to use the AI Broker feature in Entrade X trading platform of individual and institutional customers are different. Although DNSE's market focus and orientation are targeting individual customers, attracting funds and businesses are still common development trends of securities companies This study has not mentioned the impact factors from institutional customers and investment funds.
This study has some limitations in data collection and processing methods As for collecting new data, we are only collecting information from people with investment capital of over 1 billion - we have not collected information from other individuals Data processing is using spss software with commonly used scales such as Cronbach's Alpha, exploratory factor analysis, correlation analysis and linear regression To apply and test the research model with higher reliability, the author suggests that future studies can use the SEM structural model because this model allows the study to simultaneously estimate the element in the overall model.
Vietnam's stock market still has a lot of room for growth and development in the future, in addition, market upgrade criteria are gradually being met, along with the goal of Vietnam's stock market being recognized by ETSE Russell Upgrading to Secondary Emerging will help attract capital, mobilize capital and attract more investors to participate in the market Therefore, developing AI features to help users simplify investment and save time is a central task in DNSE's strategy and mission.
Based on the limitations of previous research, the author proposes some research directions in this field.
Expanding the scope of research, can do more research on other subjects such as students and investors with total investment capital of less than 1 billion In addition, it can be expanded to include corporate customers and investment funds for broader coverage and more accurate reflection At the same time, it is possible to expand the study of influencing factors instead of 7 factors as in this study.
In addition, empirical research can be strengthened to clarify the relationship between the intention to use the Feature AI Broker feature and the behavior of using Feature AI Broker of customers and investors Because from intention to actual use is influenced by many factors Meanwhile, the ultimate goal that the company is aiming for is to attract customers to use and pay for the AI Broker feature.
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APPENDIX 1: QUESTIONNAIRE SURVEY Hello Sir/Madam
Thank you very much for taking the time to participate in the survey
Below is a consumer behavior research survey with the topic "Research on factors affecting the intention to use the AI Broker feature on the Entrade X trading platform", this is the feature customers use Use AI technologies to receive advice and receive market information automatically and quickly.
The answer plays a very important role for the author I hope you can complete it seriously Each opinion is useful information and worth researching.
Wishing you happiness and success.
Below are statements about factors that influence the intention to use the AI Broker feature on the Entrade X trading platform Please indicate your level of agreement in increasing order from | to 5.
Symbol | Observable variables under the factor; 1| 2| 3| 4| 5
PEI I find the Future AI Brokeruseful in stock investing PE2 I can save time using Future AI Broker in collecting investment information PE3 Using the Future AI Brokerfor investing saves me time and is more efficient than doing my own research and research
Symbol | Observable variables under the factor
EEI Learning how to use the Future AI Broker in the
Entrade X trading platform was easy for me EE2 I find the Future AI Broker in the Entrade X trading platform easy to use EE3 It doesn't take much effort for me to master the
Future AI Broker in the Entrade X trading platform
Symbol | Observable variables under the factor
Sil My family and relatives encouraged me to use
AI Broker on Entrade X SI2 Friends, colleagues, customers encourage me to use AI Broker on Entrade X
SB Where I live, study and work recommend me to use AI Broker on Entrade X Symbol | Observable variable under the factor
FCI I have the necessary equipment (phone connected to wifi, 3g), tablet, laptop to be able to use the AI broker feature FC2 Future AI Brokeris similar to consulting feature from human brokers of securities companies FC3 How to handle problems with the AI Broker feature
Symbol | Observable variable under the factor
HMI For me, using the AI Broker feature helps me save time instead of reading reports and listening to advice
HM2 I will prioritize Future AI Broker in Entrade X stock trading platform if I receive quick information, good profitable advice
HM3 I like the Future AI Broker in the Entrade X stock trading platform instead of having to listen to traditional advisory teams Symbol | Observable variables under the factor
PVI I can save time and profit by using Future AI
Broker in Entrade X trading platform PV2 Future AI Broker in Entrade X trading platform helps me use my money more rationally PV3 Future AI Broker in Entrade X trading platform provides valuable promotions for me Symbol | Observable variables of the factor “Trust”
TH I think the Future AI Broker in Entrade X trading platform is quite popular and reliable TT2 I believe in the safety of the Future AI Broker in the Entrade X trading platform TT3 I do not doubt the security of the Future AI
Symbol | Observable variables under the factor
IUI I plan to use Future AI Broker in Entrade X trading platform in the future
IU2 I plan to regularly use the Future AI Broker In the Entrade X app IU3 My intention is to use Future AI Broker in
Entrade X trading platform rather than using any other alternative
IU4 I will encourage others to use the Future AI
2 Please tell us your age?
3 Please indicate your current educational level?
4 Please tell us your current occupation?
5 Please tell us your current monthly income?
From 30 million VND to under 40 million VND
From 20 million VND to under 30 million VND Over 30 million VND
Sincerely thank you and wish you success in life!