Page 5 Visual Data:
- Description: [IMAGE ANALYSIS]
This image appears to be a page from a technical or academic document, specifically a research paper or a technical report. The page is divided into several sections, each containing text and diagrams. Here is a detailed description of the content:

### Top Section
- **Title**: The title at the top of the page is not clearly visible, but it seems to be related to the content of the document.
- **Author**: The author's name is not visible, but it is likely to be "Đỗ Quang Hùng".

### Main Body
- **Text**: The main body of the page contains a block of text that appears to be a discussion or explanation of a technical concept or methodology. The text is written in Vietnamese and is formatted in a clear, readable manner.
- **Flowchart**: There is a flowchart on the right side of the page, which appears to be a diagram illustrating a process or algorithm. The flowchart includes various steps and connections between different components, which might be related to the text on the left side.

### Section 4: Results and Analysis
- **Text**: This section contains a detailed analysis or results of a study or experiment. The text is written in Vietnamese and is formatted in a clear, readable manner.
- **Heatmap**: There is a heatmap on the right side of the page, which is a graphical representation of data. The heatmap shows a color-coded matrix of data points, with different colors representing different values or categories. The color gradient indicates the magnitude of the data points, with lighter colors representing lower values and darker colors representing higher values.

### Section 4.1: Analysis
- **Text**: This section provides a detailed analysis of the results or findings. The text is written in Vietnamese and is formatted in a clear, readable manner.
- **Heatmap**: There is a heatmap on the right side of the page, which is a graphical representation of data. The heatmap shows a color-coded matrix of data points, with different colors representing different values or categories. The color gradient indicates the magnitude of the data points, with lighter colors representing lower values and darker colors representing higher values.

### Section 4.2: Conclusion
- **Text**: This section provides a conclusion or summary of the findings. The text is written in Vietnamese and is formatted in a clear, readable manner.
- **Heatmap**: There is a heatmap on the right side of the page, which is a graphical representation of data. The heatmap shows a color-coded matrix of data points, with different colors representing different values or categories. The color gradient indicates the magnitude of the data points, with lighter colors representing lower values and darker colors representing higher values.

### Section 4.3: References
- **Text**: This section lists references or sources used in the document. The text is written in Vietnamese and is formatted in a clear, readable manner.
- **Heatmap**: There is a heatmap on the right side of the page, which is a graphical representation of data. The heatmap shows a color-coded matrix of data points, with different colors representing different values or categories. The color gradient indicates the magnitude of the data points, with lighter colors representing lower values and darker colors representing higher values.

### Overall Analysis
This page appears to be a technical or academic document, possibly a research paper or a technical report. The text and diagrams are formatted in a clear, readable manner, and the use of a heatmap suggests that the document may be related to data analysis or statistical methods. The presence of a flowchart and a conclusion section indicates that the document is structured to provide a comprehensive overview of the findings and methodology used in the research.
- Text Content: [IMAGE ANALYSIS]
The image is a page from a document, likely a research paper or academic article. The page number is 18, as indicated at the bottom. The document is written in Vietnamese and appears to be structured in a logical and coherent manner. Here is a detailed description of the page:

### Header:
- **Title**: TẬP CHÍ KHOA HỌC VÀ CÔNG NGHỆ TRƯỜNG ĐẠI HỌC HƯNG VƯỜNG
- **Author**: Đỗ Quang Hùng

### Main Content:
The main content of the page is divided into two main sections: text and a flowchart.

#### Text Section:
The text is written in paragraphs and discusses various statistical measures and techniques used in data analysis. The text is organized in a logical flow, starting with an introduction to statistical measures like RMSE, MAE, and MAPE, followed by a discussion on how these measures are used to evaluate the performance of a model. The text then moves on to explain the use of MAPE for evaluating the accuracy of a model, and how it is calculated. The text also mentions the use of Random Forest, XGBoost, and MLP (Neural Network) for model evaluation.

#### Flowchart Section:
The flowchart section is a visual representation of the process used to evaluate the performance of a model. It starts with the input data, which is then processed through various steps, including data cleaning, feature selection, and model evaluation. The flowchart includes steps such as data preprocessing, feature engineering, model training, and model evaluation. The flowchart is designed to illustrate the sequence of steps involved in the evaluation process.

### Additional Elements:
- **Hình 1. Các bước xây dựng mô hình dự báo**: This section is a flowchart that illustrates the steps involved in building a predictive model.
- **Hình 2. Biểu đồ nhiệt độ: Heatmap**: This section shows a heatmap, which is a graphical representation of the relationships between variables. The heatmap is color-coded, with different colors representing different values. The heatmap is used to visualize the correlation between different variables.

### Analysis:
The document appears to be a technical or academic paper, likely discussing statistical methods and their applications in data analysis. The flowchart section is particularly useful for understanding the sequence of steps involved in building a predictive model. The text section provides a detailed explanation of the statistical measures used and their applications, which is crucial for anyone working with data analysis.

### Conclusion:
This page provides a comprehensive overview of statistical measures and techniques used in data analysis, along with a visual representation of the evaluation process. The flowchart section is particularly useful for understanding the sequence of steps involved in building a predictive model, making it a valuable resource for anyone working with data analysis.


Page 6 Visual Data:
- Description: [IMAGE ANALYSIS]
This image appears to be a page from a technical or academic document, specifically a research paper or report. The page number is 19, and it is part of a larger document titled "TAP CHI KHOA HOC VÀ CONG NGHÈ TRƯỜNG ĐẠI HỌC HƯNG VƯONG" (TAP CHI KHOA HOC AND CONG NGHÈ TRƯỜNG UNIVERSITY OF HUNG VƯONG).

The content of the page is divided into several sections, each discussing different aspects of a study or analysis. Here is a detailed description of the content:

1. **Title Section**: The title is "4.2. KET QUÁ ĐỰ BÁO" (4.2. ESTIMATION), which translates to "4.2. Estimation" in English. This section likely discusses the estimation methods used in the study.

2. **Table of Results**: The table is titled "Bảng 2. KET QUÁ ĐỰ BÁO ROA" (Table 2. ESTIMATION OF ROA). This table shows the results of various estimation methods for ROA (Return on Assets). The table includes columns for different methods such as Random Forest, XGBoost, and MLP (Neural Network). The rows show the results for each method, including Root Mean Squared Error (RMSE), Mean Absolute Error (MAE), Mean Absolute Percentage Error (MAPE), Pearson Correlation Coefficient (Pearson Correlation R), and Theil's U.

3. **Graphs and Charts**: There are several graphs and charts in the table, which are likely visual representations of the data. These charts include scatter plots, bar charts, and histograms, which help in visualizing the relationships between different variables.

4. **Discussion Section**: The discussion section follows the table of results, providing insights into the performance of the different estimation methods. It likely discusses the accuracy, precision, and reliability of each method.

5. **Conclusion Section**: The conclusion section summarizes the findings and provides a final statement about the study's results.

The overall content of the page appears to be focused on statistical analysis and estimation techniques, specifically in the context of ROA estimation. The use of tables, graphs, and charts helps in presenting the data in a clear and concise manner, making it easier for readers to understand the results and conclusions of the study.
- Text Content: [IMAGE ANALYSIS]
The image is a page from a document, specifically from a book or academic paper. The page number is 19, and the document is titled "TAP CHI KHOA HOC VÀ CONG NGHỆ TRƯỜNG ĐẠI HỌC HƯNG VƯONG" (TAP CHI KHOA HỌC VÀ CÔNG NGHỆ TRƯỜNG ĐẠI HỌC HƯNG VƯONG). The page number is 14-24, indicating it is part of a larger document.

The content of the page is divided into several sections, each containing text and graphical data. Here is a detailed description of the page:

### Header:
- **Title**: TAP CHI KHOA HỌC VÀ CÔNG NGHỆ TRƯỜNG ĐẠI HỌC HƯNG VƯONG
- **Page Number**: 14-24

### Main Content:
1. **Introduction Section**:
   - The text discusses the impact of various economic indicators on the ROE (Return on Equity) of different industries in Vietnam. It mentions that the ROE is influenced by factors such as CPI (Consumer Price Index), USD-VND Exchange Rate, Gold Price, WTI Oil Price, and Brent Oil Price.

2. **Graphical Data**:
   - **Graph 2**: **Kết quả dự báo ROA**
     - **Columns**:
       - **Mô hình**: Random Forest, XGBoost, MLP (Neural Network)
       - **RMSE**: 0.0926, 0.0992, 0.1031
       - **MAPE**: 73.5290, 40.2614, 66.2759
       - **MAE**: 0.0742, 0.0735, 0.0830
       - **Pearson Correlation R**: 0.9079, 0.8975, 0.8864
       - **Theil’s U**: 0.0929, 0.1000, 0.1045
     - **Legend**:
       - **Random Forest**: Blue dots
       - **XGBoost**: Red dots
       - **MLP (Neural Network)**: Green dots
     - **Axes**:
       - **X-axis**: Mô hình
       - **Y-axis**: RMSE, MAPE, MAE, Pearson Correlation R, Theil’s U

3. **Graph 3**: **Giá trị thực tế và dự báo ROA**
   - **Columns**:
     - **Mô hình**: Random Forest, XGBoost
     - **Giá trị thực tế**: 0, 0.05, 0.1, 0.15, 0.2, 0.25
     - **Giá trị dự báo**: 0.05, 0.1, 0.15, 0.2, 0.25
     - **Legend**:
       - **Random Forest**: Green bars
       - **XGBoost**: Red bars
     - **Axes**:
       - **X-axis**: Mô hình
       - **Y-axis**: Giá trị thực tế, Giá trị dự báo

4. **Graph 4**: **Giá trị thực tế và dự báo ROA**
   - **Columns**:
     - **Mô hình**: Random Forest, XGBoost
     - **Giá trị thực tế**: 0, 0.05, 0.1, 0.15, 0.2, 0.25
     - **Giá trị dự báo**: 0.05, 0.1, 0.15, 0.2, 0.25
     - **Legend**:
       - **Random Forest**: Green bars
       - **XGBoost**: Red bars
     - **Axes**:
       - **X-axis**: Mô hình
       - **Y-axis**: Giá trị thực tế, Giá trị dự báo

### Analysis:
- **Random Forest**: The Random Forest model has the lowest RMSE, MAPE, MAE, Pearson Correlation R, and Theil’s U values.
- **XGBoost**: The XGBoost model has the highest RMSE, MAPE, MAE, Pearson Correlation R, and Theil’s U values.
- **MLP (Neural Network)**: The MLP (Neural Network) model has the highest RMSE, MAPE, MAE, Pearson Correlation R, and Theil’s U values.

### Conclusion:
The study


Page 7 Visual Data:
- Description: [IMAGE ANALYSIS]
This image appears to be a page from a technical or academic document, specifically a research paper or a report. The page is divided into several sections, each containing different types of graphical and textual data. Here is a detailed description of the content:

### Top Section:
- **Title**: "TẬP CHÍ KHOA HỌC VÀ CÔNG NGHỆ TRƯỜNG ĐẠI HỌC HƯNG VƯỜNG" (Study of Research and Engineering in the University of Hung Vuong)
- **Author**: Đỗ Quang Hưng (Author)

### Main Graph:
- **Title**: "MLP (Neural Network) - Giá trị thực tế và giá trị dự báo của ROA"
- **Axes**:
  - **X-axis**: Represents the "Thực tế" (Actual).
  - **Y-axis**: Represents the "Giá trị dự báo" (Predicted Value).

### Sub-Sections:
1. **Graph 1**:
   - **Title**: "Sai số dự báo"
   - **Axes**:
     - **X-axis**: Represents the "Mẫu" (Sample).
     - **Y-axis**: Represents the "Sai số dự báo" (Error Rate).

2. **Graph 2**:
   - **Title**: "Phân bố sai số"
   - **Axes**:
     - **X-axis**: Represents the "Giá trị sai số" (Error Rate).
     - **Y-axis**: Represents the "Số lượng" (Number of Observations).

### Textual Content:
- **Hình 5. Giá trị thực tế và dự báo ROA của MLP (Neural Network)**:
  - **Caption**: "Hình 5. Giá trị thực tế và dự báo ROA của MLP (Neural Network)"
  - **Explanation**: This section discusses the relationship between the actual ROA values and the predicted ROA values using a neural network (MLP).
  - **Context**: The text mentions that the neural network (MLP) is used to predict the ROA values based on various inputs.

### Table:
- **Title**: "Bảng 3. Kết quả dự báo ROE"
  - **Columns**:
    - **Mô hình**: Represents the different models used.
    - **RMSE**: Represents the Root Mean Squared Error.
    - **MAPE**: Represents the Mean Absolute Percentage Error.
    - **MAE**: Represents the Mean Absolute Error.
    - **Pearson Correlation R**: Represents the Pearson correlation coefficient.
    - **Theil’s U**: Represents Theil’s U index.

### Additional Information:
- **Footer**: The page number is 20.
- **Author**: The author is Đỗ Quang Hưng.

### Analysis:
This page appears to be part of a research paper or report that focuses on the application of neural networks (MLP) in predicting ROA (Return on Assets) values. The graphs and tables provide insights into the accuracy and performance of the neural network model in predicting ROA values. The text explains the relationship between actual ROA values and predicted ROA values, which is crucial for financial analysis and decision-making.

### Conclusion:
This page is a valuable resource for anyone interested in the application of neural networks in financial modeling. The detailed graphs and tables provide a clear understanding of the model's performance, which can be used to evaluate the accuracy and reliability of the neural network model in predicting ROA values.
- Text Content: [IMAGE ANALYSIS]
The image is a page from a document, likely a research paper or academic report, discussing the application of neural networks in financial modeling. The page is divided into several sections, each containing different types of graphical and tabular data.

### Top Section:
- **Title**: TẬP CHÍ KHOA HỌC VÀ CÔNG NGHỆ TRƯỜNG ĐẠI HỌC HƯNG VƯỜNG
- **Author**: Đỗ Quang Hưng

### Middle Section:
- **Graph 1**: Scatter Plot
  - **Title**: MLP (Neural Network) - Giá trị thực tế và giá trị dự báo của ROA
  - **Axes**:
    - **X-axis**: Mẫu
    - **Y-axis**: Giá trị dự báo
  - **Data Points**: Blue dots representing actual values and a solid line representing the predicted values.

- **Graph 2**: Scatter Plot
  - **Title**: Sai số dự báo
  - **Axes**:
    - **X-axis**: Mẫu
    - **Y-axis**: Sai số dự báo
  - **Data Points**: Red dots representing actual values and a dashed line representing the predicted values.

- **Graph 3**: Bar Chart
  - **Title**: Phân bố sai số
  - **Axes**:
    - **X-axis**: Giá trị sai số
    - **Y-axis**: Số lượng
  - **Data Bars**: Green bars representing the number of instances with each level of sai số.

### Bottom Section:
- **Table**: Table 3. Kết quả dự báo ROE
  - **Columns**:
    - **Mô hình**: Various models
    - **RMSE**: Root Mean Squared Error
    - **MAPE**: Mean Absolute Percentage Error
    - **MAE**: Mean Absolute Error
    - **Pearson Correlation R**: Pearson correlation coefficient
    - **Theil’s U**: Theil’s U index
  - **Rows**:
    - **Random Forest**: 0,0811
    - **XGBoost**: 0,0920
    - **MLP (Neural Network)**: 0,1068

### Additional Information:
- **Footer**: The page number is 20.
- **Language**: Vietnamese.

### Analysis:
The document appears to be discussing the performance of different models (Random Forest, XGBoost, and MLP (Neural Network)) in predicting ROA (Return on Assets) using neural networks. The graphs and table provide visual and quantitative insights into the accuracy and performance of these models. The scatter plots and bar chart help in understanding the distribution of errors and the correlation between actual and predicted values. The table provides a comparative analysis of the models' performance metrics, such as RMSE, MAPE, MAE, Pearson Correlation R, and Theil’s U, which are crucial for evaluating the effectiveness of the models in predicting ROA.

Overall, the document is a detailed analysis of neural network models in financial forecasting, highlighting their strengths and weaknesses in predicting ROA.


Page 8 Visual Data:
- Description: [IMAGE ANALYSIS]
This image is a page from a technical document, specifically from a textbook or academic paper. The page number is 21, and it appears to be part of a larger study or research paper. The title at the top of the page reads "TAP CHI KHOA HOC VÀ CONG NGHE TRUONG DAI HOC HUNG VUONG" which translates to "Study of the Research and Engineering Department of the University of Hung Vuong."

The page contains several graphs and charts, each representing different data points or results. Here is a detailed description of each section:

1. **Graph 1 (Random Forest)**:
   - This graph shows a scatter plot with two sets of data points. The x-axis represents the "Thực tế" (Actual), and the y-axis represents the "Đủ bảo" (Coverage). The data points are connected by a line, indicating a positive correlation between the two variables.

2. **Graph 2 (XGBoost)**:
   - Similar to the Random Forest graph, this graph also shows a scatter plot with two sets of data points. The x-axis represents the "Thực tế" (Actual), and the y-axis represents the "Đủ bảo" (Coverage). The data points are connected by a line, indicating a positive correlation between the two variables.

3. **Graph 3 (Sai số dự báo)**:
   - This graph shows a scatter plot with two sets of data points. The x-axis represents the "Mẫu" (Sample), and the y-axis represents the "Sai số dự báo" (Error Rate). The data points are connected by a line, indicating a positive correlation between the "Mẫu" (Sample) and the "Sai số dự báo" (Error Rate).

4. **Graph 4 (Phân bố sai số)**:
   - This graph shows a bar chart with two categories. The x-axis represents the "Giá trị sai số" (Error Value), and the y-axis represents the "Số lượng" (Number). The bars are colored green, and the data points are connected by a line, indicating a positive correlation between the "Giá trị sai số" (Error Value) and the "Số lượng" (Number).

5. **Graph 5 (Hình 6. Giá trị thực tế và dự báo ROE của Random Forest)**:
   - This graph shows a scatter plot with two sets of data points. The x-axis represents the "Giá trị sai số" (Error Value), and the y-axis represents the "Đủ bảo" (Coverage). The data points are connected by a line, indicating a positive correlation between the "Giá trị sai số" (Error Value) and the "Đủ bảo" (Coverage).

6. **Graph 6 (Hình 7. Giá trị thực tế và dự báo ROE của XGBoost)**:
   - Similar to the Random Forest graph, this graph also shows a scatter plot with two sets of data points. The x-axis represents the "Giá trị sai số" (Error Value), and the y-axis represents the "Đủ bảo" (Coverage). The data points are connected by a line, indicating a positive correlation between the "Giá trị sai số" (Error Value) and the "Đủ bảo" (Coverage).

7. **Graph 7 (Hình 8. Giá trị thực tế và dự báo ROE của MLP (Neural Network)**:
   - This graph shows a scatter plot with two sets of data points. The x-axis represents the "Giá trị sai số" (Error Value), and the y-axis represents the "Đủ bảo" (Coverage). The data points are connected by a line, indicating a positive correlation between the "Giá trị sai số" (Error Value) and the "Đủ bảo" (Coverage).

8. **Graph 8 (Hình 9. Giá trị thực tế và dự báo ROE của MLP (Neural Network)**:
   - Similar to the Random Forest graph, this graph also shows a scatter plot with two sets of data points. The x-axis represents the "Giá trị sai số" (Error Value), and the y-axis represents the "Đủ bảo" (Coverage). The data points are connected by a line, indicating a positive correlation between the "Giá trị sai số" (Error Value) and the "Đủ bảo" (Coverage).

The text on the page provides the source of the data and the methodology used to analyze the results. The overall theme of the page is focused on the correlation between different variables, specifically ROE (Return on Equity) and the coverage of predictions or forecasts.
- Text Content: [IMAGE ANALYSIS]
The image is a page from a document, likely a textbook or academic paper, discussing the relationship between the real test results and the ROE (Return on Equity) of different models. The page is divided into several sections, each containing graphs and bar charts. Here is a detailed description of the layout and content:

### Header:
- **Title**: TẬP CHÍ KHOA HỌC VÀ CÔNG NGHỆ TRƯỜNG ĐẠI HỌC HƯNG VƯỜNG
- **Section**: Tập 11, Số 2 (2025): 14 - 24

### Main Content:
1. **Graphs and Charts**:
   - **Graph 1**: Random Forest - Giá trị thực tế và độ bảo của ROE
   - **Graph 2**: XGBoost - Giá trị thực tế và độ bảo của ROE
   - **Graph 3**: Sai số dự báo
   - **Graph 4**: Sai số dự báo
   - **Graph 5**: Phân bố sai số
   - **Graph 6**: Giá trị thực tế và độ bảo ROE của Random Forest
   - **Graph 7**: Giá trị thực tế và độ bảo ROE của XGBoost
   - **Graph 8**: Giá trị thực tế và độ bảo ROE của MLP (Neural Network)

2. **Bar Charts**:
   - **Bar Chart 1**: Giá trị thực tế và độ bảo ROE của Random Forest
   - **Bar Chart 2**: Giá trị thực tế và độ bảo ROE của XGBoost
   - **Bar Chart 3**: Giá trị thực tế và độ bảo ROE của MLP (Neural Network)

### Text:
- **Hình 6. Giá trị thực tế và độ bảo ROE của Random Forest**
  - **Nguồn**: Tác giả tinh toàn

- **Hình 7. Giá trị thực tế và độ bảo ROE của XGBoost**
  - **Nguồn**: Tác giả tinh toàn

- **Hình 8. Giá trị thực tế và độ bảo ROE của MLP (Neural Network)**
  - **Nguồn**: Tác giả tinh toàn

### Footer:
- **Page Number**: 21

### Analysis:
The page provides a comparative analysis of the real test results and ROE for different models, specifically Random Forest, XGBoost, and MLP (Neural Network). Each graph and chart visually represents the relationship between the real test results and ROE, with the x-axis representing the ROE and the y-axis representing the real test results. The graphs and charts are color-coded to distinguish between different models, and the bar charts provide a visual representation of the data.

### Conclusion:
The page serves as a visual and analytical tool to help readers understand the performance of different models in predicting ROE. By comparing the graphs and charts, readers can gain insights into which model performs better in terms of accuracy and reliability in predicting ROE.


Page 9 Visual Data:
- Description: [IMAGE ANALYSIS]
This image appears to be a page from a book or academic paper, specifically page 22. The text is in Vietnamese and discusses various statistical and machine learning concepts. The page number is visible at the bottom, indicating it is part of a larger document. The content is organized into sections, with headings and subheadings, suggesting it is part of a larger study or research paper.

### Key Points from the Text:
1. **Random Forest and XGBoost**:
   - The text mentions Random Forest and XGBoost, two popular machine learning algorithms.
   - It compares their performance in terms of accuracy, RMSE, MAE, and R-squared values.
   - The authors highlight the strengths and weaknesses of each algorithm, suggesting that Random Forest is better suited for tasks requiring high accuracy and low variance, while XGBoost is better for tasks requiring high speed and scalability.

2. **MLP (Multilayer Perceptron)**:
   - The text discusses MLP, another type of neural network.
   - It mentions that MLP has a higher RMSE and R-squared value compared to Random Forest and XGBoost.
   - The authors suggest that MLP is more suitable for tasks requiring high accuracy and high precision.

3. **Ensemble Learning**:
   - The text mentions ensemble learning, which combines multiple models to improve overall performance.
   - It discusses Random Forest and XGBoost as examples of ensemble learning.
   - The authors suggest that ensemble learning can improve the robustness and generalization of machine learning models.

4. **Machine Learning Applications**:
   - The text mentions various applications of machine learning, including financial forecasting, image recognition, and natural language processing.
   - It highlights the importance of machine learning in modern industries and suggests that it is a rapidly evolving field with many applications.

### Conclusion:
This page from the book or academic paper provides a detailed comparison of Random Forest, XGBoost, and MLP, along with an overview of ensemble learning and its applications. The text is technical and focused on machine learning, making it a valuable resource for anyone interested in the field.
- Text Content: [IMAGE ANALYSIS]
The image is a page from a document, specifically from a Vietnamese academic or professional publication. The page number is 22, as indicated at the bottom right corner. The document appears to be a research paper or a technical report, given the formal layout and structured content.

The page is divided into two main sections, each containing a significant amount of text. The left section is titled "Bảng 3 trình bày kết quả dự báo ROE," which translates to "Table 3 presenting the results of ROE prediction." The right section is titled "5. Kết luận," which translates to "5. Conclusion."

The content of the page is organized into paragraphs, each containing detailed information and analysis. The text is written in Vietnamese, and the formatting includes headings, subheadings, and bullet points to organize the information clearly.

Here is a detailed breakdown of the content:

### Table 3: Presenting the Results of ROE Prediction
- **Introduction**: Discusses the importance of ROE (Return on Equity) in financial analysis.
- **Methodology**: Describes the methods used to predict ROE, including Random Forest, XGBoost, and MLP (Multi-Layer Perceptron).
- **Results**: Compares the performance of these models using metrics such as RMSE (Root Mean Squared Error), MAE (Mean Absolute Error), and R-squared (R²).
- **Conclusion**: Summarizes the findings and discusses the implications of the results.

### 5. Kết luận
- **Introduction**: Discusses the importance of AI in financial analysis and the role of machine learning models in predicting ROE.
- **Methods**: Describes the use of Random Forest, XGBoost, and MLP models for ROE prediction.
- **Results**: Compares the performance of these models using metrics such as RMSE, MAE, and R-squared.
- **Conclusion**: Discusses the effectiveness of the models in predicting ROE and their potential applications in financial decision-making.

### Table 3: Presenting the Results of ROE Prediction
- **Introduction**: Discusses the importance of ROE in financial analysis.
- **Methodology**: Describes the methods used to predict ROE, including Random Forest, XGBoost, and MLP.
- **Results**: Compares the performance of these models using metrics such as RMSE (Root Mean Squared Error), MAE (Mean Absolute Error), and R-squared (R²).
- **Conclusion**: Summarizes the findings and discusses the implications of the results.

### 5. Kết luận
- **Introduction**: Discusses the importance of AI in financial analysis and the role of machine learning models in predicting ROE.
- **Methods**: Describes the use of Random Forest, XGBoost, and MLP models for ROE prediction.
- **Results**: Compares the performance of these models using metrics such as RMSE, MAE, and R-squared.
- **Conclusion**: Discusses the effectiveness of the models in predicting ROE and their potential applications in financial decision-making.

The page is well-organized, with clear headings and subheadings to guide the reader through the content. The text is formatted in a way that is typical for academic or professional publications, with a focus on providing detailed information and analysis.


Page 10 Visual Data:
- Description: [IMAGE ANALYSIS]
This image appears to be a page from a book or academic journal, specifically page 23 of a document titled "Tập Chí Khoa Học Và Công Nghệ Trường Đại Học Hùng Vương". The page is divided into two columns, each containing a list of references. The references are organized in a structured format, with each reference listed in a separate line. The references are numbered from 1 to 11, and each reference is accompanied by a corresponding author's name, title, and publication year.

Here is the formatted list of references from the page:

1. [1] Kayakus M., Tutcu B., Terzioglu M., Talaş H. & Ünal Uyar G. F. (2023). ROA and ROE forecasting in iron and steel industry using machine learning techniques for sustainable profitability. Sustainability, 15(9), 1-14.
2. [2] Tutcu B., Kayakus M., Terzioglu M., Ünal Uyar G. F., Talaş H. & Yetiz F. (2024). Predicting financial performance in the IT industry with machine learning: ROA and ROE analysis. Applied Sciences, 14(17), 1-16.
3. [3] Son P. V. H. & Duong L. T. (2024). Research on applying machine learning models to predict and assess return on assets (ROA). Asian Journal of Civil Engineering, 25(5), 4269-4279.
4. [4] Das A., De S., Mukherjee T., Dey M. & Das Ghosh K. (2024). Forecasting bank ROE with gradient boosting: a machine learning approach. Proceedings of the 5th International Conference on Data Intelligence and Cognitive Informatics (ICDICI), 448-452.
5. [5] Balci T. & Ogul H. (2021). Predicting bank return on equity (ROE) using neural networks. Proceedings of the IEEE 19th World Symposium on Applied Machine Intelligence and Informatics (SAMI), 279-286.
6. [6] He K., Yang Q., Ji L., Pan J. & Zou Y. (2023). Financial time series forecasting with the deep learning ensemble model. Mathematics, 11(4), 1054.
7. [7] Nguyễn Phát Đạt, Hồ Mai Minh Nhật, Trương Công Vinh, Lê Quang Chân Phong & Lê Hoàn Sư (2025). Úng dụng học máy và học sâu trong nghiên cứu tài chính: Một nghiên cứu về dự báo khả năng hoạt động của khách hàng. Tập chí Khoa học Đại học Mô Thanh phố Hồ Chí Minh - Kinh tế và Quản trị kinh doanh, 20(1), 35-53.
8. Nguyễn Minh Nhật & Ngô Hoàng Khánh Duy (2024). Dự báo khả năng hoạt động của doanh nghiệp nhỏ và vừa tại Việt Nam: Nghiên cứu cụ thể trên các mô hình học máy. Tập chí Kinh tế - Luật & Ngân hàng, 266, 51-64.
9. Iranzad R. & Liu X. (2024). A review of random forest-based feature selection methods for data science education and applications. International Journal of Data Science and Analytics. 2024, 1-15.
10. Liu X., Hu Y., Li X., Du R., Xiang Y., Zhang F. (2024). An interpretable model for salinity inversion assessment of the South Bank of the Yellow River based on Optuna hyperparameter optimization and XGBoost. Agronomy, 15(18), 1-19.
11. Almahadeen L., ALMahadin G., Santosh K., Aarif M., Deb P., Syamala M. & Bala B. K. (2024). Enhancing threat detection in financial cyber security through auto encoder-MLP hybrid models. International Journal of Advanced Computer Science and Applications, 15(4), 924-933.

The page provides a comprehensive list of references related to various academic and research topics, including machine learning, finance, and data science. The references are organized in a clear and structured manner, making it easy for readers to locate specific information.
- Text Content: [IMAGE ANALYSIS]
The image is a page from a book or academic journal, specifically page 23 of a document. The page number is located at the bottom right corner of the page. The text is in Vietnamese and appears to be a section of a research paper or academic article. The layout is typical of academic publications, with paragraphs of text separated by lines and paragraphs. The text is formatted in a standard academic style, with justified alignment of the text and justified spacing between paragraphs. The font is clear and legible, with a consistent size throughout the page. There are no images, tables, or figures present on this page. The page number "23" is clearly visible at the bottom right corner, indicating that this is the 23rd page of the document.


Page 5 Visual Data:
- Description: [IMAGE ANALYSIS]
This image appears to be a page from a book or academic paper, specifically page 57 of a document titled "Kieu Anh Tai va cong su." The text is in Vietnamese and discusses various topics related to technology and business. Here is a detailed description of the content:

1. **Title and Page Number**: The title is "Kieu Anh Tai va cong su." The page number is 57.

2. **Content Overview**:
   - The text is divided into several paragraphs, each discussing different aspects of technology and business.
   - The paragraphs are numbered, starting from H1b and continuing to H3b.
   - The content appears to be discussing the integration of technology (EC, ET, ER, DG) in various business contexts.

3. **Key Points**:
   - **EC (Electronic Commerce)**: The text mentions EC as a key component in business operations.
   - **ET (Electronic Trading)**: It discusses how ET is integrated into business processes.
   - **ER (Electronic Retailing)**: The text also touches on ER, highlighting its role in business operations.
   - **DG (Digital Goods)**: The discussion includes DG, which is mentioned as a significant aspect of business.
   - **ST (Supply Chain Management)**: The text briefly touches on ST, which is also mentioned as a key aspect of business operations.

4. **Additional Information**:
   - The text includes references to specific studies and sources, such as "Brennen & Kreiss, 2016," "Ritter & Pedersen, 2020," and "Nguyen & ctg., 2022."
   - The text is structured in a way that suggests it is part of a larger study or research paper.

5. **Visual Elements**:
   - The text is in Vietnamese, which is a language spoken in Vietnam.
   - The formatting is typical of academic writing, with paragraphs and numbered sections.

6. **Conclusion**:
   - The overall theme of the text is the integration of technology in business operations, with a focus on electronic commerce, electronic trading, electronic retailing, digital goods, and supply chain management.

This description should provide a comprehensive understanding of the content and structure of the page, which is relevant for anyone looking to understand the discussion on technology and business integration.
- Text Content: [IMAGE ANALYSIS]
The image is a page from a document, specifically from a research paper or academic article. The page number is 57, and the title of the document is "Kieu Anh Tai va cong su." The content appears to be in Vietnamese and discusses various topics related to technology and business. Here is a detailed description of the content:

1. **Header Information:**
   - The top of the page contains the title of the document, which is partially visible.
   - Below the title, there is a page number: 57.

2. **Main Body:**
   - The main body of the text is divided into several paragraphs, each discussing different aspects of technology and business.
   - The paragraphs are numbered, starting from H1b and continuing to H3b.
   - The text is written in a clear and concise manner, with each paragraph providing a specific point or topic.

3. **Highlighted Sections:**
   - There are several highlighted sections in the text, which are likely to be important or emphasize certain points.
   - These highlighted sections are marked with different colors, such as blue and red, to draw attention to specific parts of the text.

4. **Content Analysis:**
   - The content appears to be discussing the integration of technology (EC, ET, ER, DG) in various business contexts.
   - Specific terms like "SaaS," "Sap," "SaaS," "SaaS," "SaaS," "SaaS," "SaaS," "SaaS," "SaaS," "SaaS," "SaaS," "SaaS," "SaaS," "SaaS," "SaaS," "SaaS," "SaaS," "SaaS," "SaaS," "SaaS," "SaaS," "SaaS," "SaaS," "SaaS," "SaaS," "SaaS," "SaaS," "SaaS," "SaaS," "SaaS," "SaaS," "SaaS," "SaaS," "SaaS," "SaaS," "SaaS," "SaaS," "SaaS," "SaaS," "SaaS," "SaaS," "SaaS," "SaaS," "SaaS," "SaaS," "SaaS," "SaaS," "SaaS," "SaaS," "SaaS," "SaaS," "SaaS," "SaaS," "SaaS," "SaaS," "SaaS," "SaaS," "SaaS," "SaaS," "SaaS," "SaaS," "SaaS," "SaaS," "SaaS," "SaaS," "SaaS," "SaaS," "SaaS," "SaaS," "SaaS," "SaaS," "SaaS," "SaaS," "SaaS," "SaaS," "SaaS," "SaaS," "SaaS," "SaaS," "SaaS," "SaaS," "SaaS," "SaaS," "SaaS," "SaaS," "SaaS," "SaaS," "SaaS," "SaaS," "SaaS," "SaaS," "SaaS," "SaaS," "SaaS," "SaaS," "SaaS," "SaaS," "SaaS," "SaaS," "SaaS," "SaaS," "SaaS," "SaaS," "SaaS," "SaaS," "SaaS," "SaaS," "SaaS," "SaaS," "SaaS," "SaaS," "SaaS," "SaaS," "SaaS," "SaaS," "SaaS," "SaaS," "SaaS," "SaaS," "SaaS," "SaaS," "SaaS," "SaaS," "SaaS," "SaaS," "SaaS," "SaaS," "SaaS," "SaaS," "SaaS," "SaaS," "SaaS," "SaaS," "SaaS," "SaaS," "SaaS," "SaaS," "SaaS," "SaaS," "SaaS," "SaaS," "SaaS," "SaaS," "SaaS," "SaaS," "SaaS," "SaaS," "SaaS," "SaaS," "SaaS," "SaaS," "SaaS," "SaaS," "SaaS," "SaaS," "SaaS," "SaaS," "SaaS," "SaaS," "SaaS," "SaaS," "SaaS," "SaaS," "SaaS," "SaaS," "SaaS," "SaaS," "SaaS," "SaaS," "SaaS," "SaaS," "SaaS," "SaaS," "SaaS," "SaaS," "SaaS," "SaaS," "SaaS," "SaaS," "SaaS," "SaaS," "SaaS," "SaaS," "SaaS," "SaaS," "SaaS," "SaaS


Page 7 Visual Data:
- Description: [IMAGE ANALYSIS]
This image is a page from a research paper, specifically from the journal "Kieu Anh Tai va cong su." The paper discusses the impact of supply chain management (SCM) on the competitiveness of a company's supply chain. The main focus is on how supply chain management (SCM) can improve the efficiency and effectiveness of a company's supply chain.

The paper presents a model that shows how supply chain management can improve the performance of a company's supply chain. The model includes several hypotheses (H1a, H1b, H2a, H2b, H3a, H3b, H4a, H4b, H5, H6a, H6b, H7a, and H7b) that are tested in the study. The hypotheses are related to the impact of supply chain management on the performance of a company's supply chain.

The paper also includes a figure that shows the relationships between the hypotheses and the performance of the company's supply chain. The figure shows how the hypotheses are interconnected and how they impact the performance of the company's supply chain.

Overall, the paper provides a comprehensive analysis of how supply chain management can improve the performance of a company's supply chain. The hypotheses and the figure provide a clear and concise way to understand the impact of supply chain management on the performance of a company's supply chain.
- Text Content: [IMAGE ANALYSIS]
The image is a page from a document, specifically from a research paper or academic article. The page number is 59, and the title of the document is "Kieu Anh Tai va cong su." The document appears to be discussing the impact of technology on business and the role of human factors in this context. Here is a detailed description of the content:

### Page Layout:
- **Header**: The top of the page contains the title of the document, which is partially visible.
- **Main Content**: The main body of the text is divided into several sections, each with a heading and a paragraph of text.
- **Graphical Representation**: There is a graphical representation of a network diagram in the middle of the page, which is labeled as "Hình 1" (Figure 1). The diagram shows various nodes and arrows connecting them, representing relationships or dependencies between different elements.
- **Subsections**: The text is divided into several subsections, each with a heading and a paragraph of text. The headings are in Vietnamese and are not translatable.

### Text Content:
1. **Introduction**: The introduction discusses the importance of human factors in the context of technology and business.
2. **Main Body**: The main body of the text is divided into several sections, each discussing different aspects of human factors and their impact on business.
3. **Graphical Representation**: The graphical representation is a network diagram that shows the relationships between different elements. The nodes represent different variables or concepts, and the arrows indicate the direction of the relationships.
4. **Subsections**: The text is divided into several subsections, each discussing a different aspect of human factors and their impact on business. The headings are in Vietnamese and are not translatable.

### Analysis:
The document appears to be a scholarly paper or research article, discussing the impact of technology on business and the role of human factors in this context. The graphical representation is a network diagram that helps to visualize the relationships between different variables or concepts. The text is divided into several subsections, each discussing a different aspect of human factors and their impact on business. The headings are in Vietnamese and are not translatable, indicating that the document is likely intended for a Vietnamese-speaking audience.

### Conclusion:
The document provides a detailed analysis of the impact of technology on business and the role of human factors in this context. The graphical representation helps to visualize the relationships between different variables, making the text more accessible and easier to understand. The use of Vietnamese headings suggests that the document is intended for a Vietnamese-speaking audience, likely in a scholarly or academic setting.


Page 8 Visual Data:
- Description: [IMAGE ANALYSIS]
This image appears to be a page from a research paper or academic article. The text is in Vietnamese and discusses various statistical data and findings related to a specific topic. Here is a detailed description of the content:

---

**Title: Kiều Anh Tài và công sự. HCMCOUJS-Kinh tế và Quản trị Kinh doanh, 20(10), 54-70**

**Page Number: 60**

---

The text is divided into several sections, each containing numerical data and statistical information. Here is a breakdown of the content:

1. **Introduction:**
   - The introduction discusses the importance of the topic and the significance of the research.
   - It mentions the authors and the journal they are affiliated with.

2. **Statistical Data:**
   - The text presents various statistical data in tables and figures.
   - The data includes:
     - **Tân số (Tân số):** 155
     - **Tỷ lệ (Tỷ lệ):** 40.2%
     - **Giới tính (Giới tính):** Nam
     - **Đồ tuổi (Đồ tuổi):** < 25
     - **Trình độ học vấn (Trình độ học vấn):** Duối Phổ thông trung học
     - **Trình độ học vấn (Trình độ học vấn):** Phổ thông trung học
     - **Trình độ học vấn (Trình độ học vấn):** Trung cấp hoặc cao đẳng nghề
     - **Trình độ học vấn (Trình độ học vấn):** Đại học trung cấp
     - **Trình độ học vấn (Trình độ học vấn):** Đại học trung cấp
     - **Trình độ học vấn (Trình độ học vấn):** Đại học trung cấp
     - **Trình độ học vấn (Trình độ học vấn):** Đại học trung cấp
     - **Trình độ học vấn (Trình độ học vấn):** Đại học trung cấp
     - **Trình độ học vấn (Trình độ học vấn):** Đại học trung cấp
     - **Trình độ học vấn (Trình độ học vấn):** Đại học trung cấp
     - **Trình độ học vấn (Trình độ học vấn):** Đại học trung cấp
     - **Trình độ học vấn (Trình độ học vấn):** Đại học trung cấp
     - **Trình độ học vấn (Trình độ học vấn):** Đại học trung cấp
     - **Trình độ học vấn (Trình độ học vấn):** Đại học trung cấp
     - **Trình độ học vấn (Trình độ học vấn):** Đại học trung cấp
     - **Trình độ học vấn (Trình độ học vấn):** Đại học trung cấp
     - **Trình độ học vấn (Trình độ học vấn):** Đại học trung cấp
     - **Trình độ học vấn (Trình độ học vấn):** Đại học trung cấp
     - **Trình độ học vấn (Trình độ học vấn):** Đại học trung cấp
     - **Trình độ học vấn (Trình độ học vấn):** Đại học trung cấp
     - **Trình độ học vấn (Trình độ học vấn):** Đại học trung cấp
     - **Trình độ học vấn (Trình độ học vấn):** Đại học trung cấp
     - **Trình độ học vấn (Trình độ học vấn):** Đại học trung cấp
     - **Trình độ học vấn (Trình độ học vấn):** Đại học trung cấp
     - **Trình độ học vấn (Trình độ học vấn):** Đại học trung cấp
     - **Trình độ học vấn (Trình độ học vấn):** Đại học trung cấp
     - **Trình độ học vấn (Trình độ học vấn):** Đại học trung cấp
     - **Trình độ học vấn (Trình độ học vấn):** Đại học trung cấp
     - **Trình độ học vấn (Trình độ học vấn):** Đại học trung cấp
     - **Trình độ học vấn (Trình độ học vấn):** Đại học trung cấp
     - **Trình độ học vấn (Trình độ học vấn):** Đại học trung cấp
     - **Trình độ học vấn (Trình độ học vấn):** Đại học trung cấp
     - **Trình độ học vấn (Trình độ học vấn):** Đại học trung cấp
     - **Trình độ học vấn (Trình độ học vấn):** Đại học trung cấp
     - **Trình độ học vấn (Trình độ học vấn):** Đại học trung cấp
- Text Content: [IMAGE ANALYSIS]
The image is a page from a document, specifically from a research paper or academic article. The page number is 60, and the title of the document is "Kiều Anh Tài và công sự. HCMCOUJS-Kinh tế và Quản trị Kinh doanh, 20(10), 54-70." The content appears to be in Vietnamese and discusses various statistical data and findings related to economic and business management.

The text is divided into several sections, each containing numerical data and descriptive text. Here is a detailed breakdown of the content:

1. **Introduction to the Data**:
   - The introduction provides context about the data being discussed, mentioning that the data is from a study conducted by Hair and colleagues (2010).
   - It states that the study found that the ratio of male to female students is 5:1, with a total of 53 students in the study.
   - The text also mentions that the study involved 265 male students and 265 female students.

2. **Statistical Analysis**:
   - The text discusses the distribution of students based on their age groups.
   - It mentions that the age groups are divided into four categories: <25, 25-34, 35-44, and >=50 years old.
   - The data shows that the majority of students are between the ages of 25-34 (45.9%).
   - The text also includes a table with the number of students in each age group.

3. **Conclusion**:
   - The conclusion summarizes the findings of the study, highlighting the importance of gender equality in education.
   - It emphasizes the need for policies and initiatives to promote gender equality in education.

The layout of the page is straightforward, with clear headings and subheadings to organize the content. The text is formatted in a typical academic style, with paragraphs and bullet points to break up the information. The use of numerical data and descriptive text makes it easy to understand the findings and implications of the study.


Page 9 Visual Data:
- Description: [IMAGE ANALYSIS]
This image is a table that provides data on various business metrics for a specific company. The table is organized into several columns and rows, with each cell containing numerical values and percentages. Here is a detailed description of the table:

### Table Description

#### Table Title:
- **Kieu Anh Tai va cong su:** This translates to "Marketing and Operations" in Vietnamese.

#### Columns:
1. **Tien so:** This column represents the total number of observations.
2. **Tien le:** This column represents the total percentage of observations.

#### Rows:
1. **Muc doanh thu trung binh cua cua hang (triệu đồng):** This translates to "Average revenue of the company (in millions of dollars)."
2. **Số nhan hoat dong cua cua hang:** This translates to "Number of active customers."
3. **Quy mo cua hang (m^2):** This translates to "Area of the company (square meters)."
4. **Số luong nhan su (nguoi):** This translates to "Number of employees."
5. **Linh vuc kinh doanh:** This translates to "Business line."
6. **Hinh thuc ban hang:** This translates to "Business model."
7. **Tong co mau hop le:** This translates to "Total customer loyalty."

#### Data:
- **Muc doanh thu trung binh cua cua hang (triệu đồng):**
  - < 50: 163 (42.2%)
  - 50 - < 100: 140 (36.3%)
  - 100 - < 200: 54 (14.0%)
  - 200 - < 500: 19 (4.9%)
  - >= 500: 10 (2.6%)

- **Số nhan hoat dong cua cua hang:**
  - < 02: 100 (25.9%)
  - 02 - < 05: 137 (35.5%)
  - 05 - < 10: 77 (19.9%)
  - 10 - < 15: 42 (10.9%)
  - >= 15: 30 (7.8%)

- **Quy mo cua hang (m^2):**
  - < 5: 25 (6.5%)
  - 5 - < 30: 84 (21.8%)
  - 30 - < 60: 222 (57.5%)
  - 60 - < 100: 34 (8.8%)
  - >= 100: 21 (5.4%)

- **Số luong nhan su (nguoi):**
  - 01: 109 (28.2%)
  - 02: 129 (33.4%)
  - 03: 70 (18.1%)
  - 04: 50 (13.0%)
  - 05: 28 (7.3%)

- **Linh vuc kinh doanh:**
  - Taphoa: 123 (31.9%)
  - Quan an, giai khat: 101 (26.2%)
  - Thoi trang, my pham & phu kien: 40 (10.4%)
  - Dien tu, do gia duong & noi that: 35 (9.1%)
  - Luong thuc, thuc pham: 25 (6.5%)
  - The thao, giai tri & du lich: 10 (2.6%)
  - Thuoc, suct khoe & thu cung: 19 (4.9%)
  - Me & be: 22 (5.7%)
  - Khac (ghi ro): 11 (2.8%)

- **Hinh thuc ban hang:**
  - Chi Online (Ban hang truc tuyen): 88 (22.8%)
  - Chi Offline (Ban hang truyen thong): 86 (22.3%)
  - Ket hop Online va Offline: 212 (54.9%)

- **Tong co mau hop le:**
  - 386 (100%)

### Analysis:
- The
- Text Content: [IMAGE ANALYSIS]
The image is a table with data organized in a structured format. The table is titled "Kieu Anh Tai va cong su." It appears to be a part of a research or survey report, specifically from the journal "HCMCOUJS-Kinh te va Quan tri Kinh doanh, 20(10), 54-70." The table is divided into several columns and rows, each containing numerical data and percentages.

### Table Description:

#### Columns:
1. **Column 1:** Represents different categories or variables.
2. **Column 2:** Represents the number of observations or cases.
3. **Column 3:** Represents the percentage of observations.

#### Rows:
1. **Row 1:** Categories or variables.
2. **Row 2:** Number of observations.
3. **Row 3:** Percentage of observations.

### Data and Percentages:
- **Row 1:**
  - Categories: < 50, 50 - < 100, 100 - < 200, 200 - < 500, >= 500
  - Observations: 163, 140, 54, 19, 10
  - Percentages: 42.2%, 36.3%, 14.0%, 4.9%, 2.6%

- **Row 2:**
  - Categories: < 02, 02 - < 05, 05 - < 10, 10 - < 15, >= 15
  - Observations: 100, 137, 77, 42, 30
  - Percentages: 25.9%, 35.5%, 19.9%, 10.9%, 7.8%

- **Row 3:**
  - Categories: < 5, 5 - < 30, 30 - < 60, 60 - < 100, >= 100
  - Observations: 25, 84, 222, 34, 21
  - Percentages: 6.5%, 21.8%, 57.5%, 8.8%, 5.4%

- **Row 4:**
  - Categories: 01, 02, 03, 04, 05
  - Observations: 109, 129, 70, 50, 28
  - Percentages: 28.2%, 33.4%, 18.1%, 13.0%, 7.3%

- **Row 5:**
  - Categories: Taphoa, Quan an, giai khat, Thoi trang, my pham & phu kien, Dien tu, do gia duong & noi that, Luong thuc, thuc pham, The thao, giai tri & du lich, Thuoc, suct khoe & thu cung, Me & be, Khac (Ghi ro)
  - Observations: 123, 101, 40, 35, 25, 25, 10, 19, 22, 11
  - Percentages: 31.9%, 26.2%, 10.4%, 9.1%, 6.5%, 6.5%, 2.6%, 4.9%, 5.7%, 2.8%

- **Row 6:**
  - Categories: Chi Online (Ban hang truc tuyen), Chi Offline (Ban hang truyen thong), Ket hop Online va Offline
  - Observations: 88, 86, 212
  - Percentages: 22.8%, 22.3%, 54.9%

- **Row 7:**
  - Categories: Tung co mau hop le
  - Observations: 386
  - Percentages: 100%

### Analysis:
The table provides data on various categories or variables, with specific observations and percentages. The data appears to be related to business or economic activities, as indicated by the categories and percentages. The percentages are calculated based on the total number of observations, which is 386.

### Conclusion:
The table provides a detailed breakdown of business activities, with specific observations and percentages for each category. The data can be used to understand the distribution and frequency of different business activities across the specified categories.


Page 10 Visual Data:
- Description: [IMAGE ANALYSIS]
This image is a page from a research paper titled "Kiều Anh Tài và công cụ HCMCOUJS-Kinh tế và Quản trị Kinh doanh, 20(10), 54-70." The page is focused on the statistical analysis of data related to economic and financial variables. The specific section of the page is titled "4.2. Dánh giá thang do," which translates to "Rating the trend."

The page contains a table with several columns and rows, detailing various statistical measures such as Cronbach's Alpha, Cronbach's Beta, and Average Variance Extracted (AVE). The table is organized into two main sections: "Bảng 2" (Table 2) and "Bảng 3" (Table 3).

In Table 2, the table is divided into two columns: "Thành phần bậc 1" (First Component) and "Hệ số tài nguyên" (Resource Load). The table includes data for different economic and financial variables, such as "Định hướng doanh nghiệp (EO)," "Định hướng đổi mới (EOI)," "Định hướng chủ động (EOP)," and "Định hướng chấp nhận rủi ro (EOR)." Each variable is listed with its corresponding Cronbach's Alpha, Cronbach's Beta, and Average Variance Extracted (AVE).

In Table 3, the table is divided into two columns: "EOI" and "EOP." The table includes data for different economic and financial variables, such as "Giá trị chức năng (VFU)," "Giá trị nhận thức (VEP)," "Giá trị cảm xúc (VEM)," "Giá trị xả hơi (VSO)," and "Giá trị điều kiện (VCO)." Each variable is listed with its corresponding Cronbach's Alpha, Cronbach's Beta, and Average Variance Extracted (AVE).

The table provides a comprehensive analysis of the reliability and validity of the data collected, which is crucial for the interpretation of the research findings. The data is presented in a clear and organized manner, making it easy for readers to understand the statistical measures and their implications.
- Text Content: [IMAGE ANALYSIS]
The image is a page from a research paper, specifically from the section titled "4.2. Dánh giá thang do". The page number is 62. The paper is titled "Kiều Anh Tài và công cụ. HCMCOUJS-Kinh tế và Quản trị Kinh doanh, 20(10), 54-70". The content is in Vietnamese and discusses the evaluation of the quality of the data and the reliability of the results.

The page contains a table with the following structure:

1. **Title**: "4.2. Dánh giá thang do"
2. **Subheading**: "Đánh giá thang do"
3. **Subheading**: "Đánh giá thang do"
4. **Subheading**: "Đánh giá thang do"
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61. **Subheading**: "Đánh giá thang do"
62. **


Page 5 Visual Data:
- Description: [IMAGE ANALYSIS]
This image is a slide from a presentation that discusses the growth and development of the Vietnamese economy. The slide is divided into two main sections: a textual section and a bar chart.

### Textual Section
The textual section provides an overview of the Vietnamese economy, highlighting its growth and development. It states that Vietnam is the 16th largest economy in the world, with a population of 98.9 million people. The population is projected to reach 100 million by 2025. The slide mentions that Vietnam is currently experiencing a rapid economic growth, with a CAGR (Compound Annual Growth Rate) of 8.8% from 2017 to 2022. It also notes that the country is facing challenges in terms of infrastructure and development, but is working towards improving these areas.

### Bar Chart
The bar chart on the right side of the slide shows the growth in the Vietnamese economy over the years. The x-axis represents the years from 2017 to 2023, while the y-axis represents the percentage of growth. The chart shows that the growth rate has been consistently high, with the highest growth rate in 2017 at 8.5%, followed by 6.1% in 2018, 6.1% in 2019, 5.1% in 2020, 4.9% in 2021, 4.3% in 2022, and 2.5% in 2023. The bar chart also includes a comparison with other countries, such as Cambodia, Indonesia, Malaysia, and Thailand, showing that Vietnam has been the fastest-growing economy in the region.

### Analysis
The slide highlights the significant growth of the Vietnamese economy, particularly in the last few years. The high growth rate of 8.8% from 2017 to 2022 is a testament to the country's economic resilience and potential. The comparison with other countries shows that Vietnam is outperforming its peers in terms of economic growth, which could be attributed to its strategic investments in infrastructure, technology, and development projects.

### Conclusion
The slide effectively communicates the economic growth and development of Vietnam, highlighting its potential for further growth and development. The high growth rate and the comparison with other countries demonstrate the country's competitive edge in the global economy. This information could be useful for businesses and investors looking to invest in Vietnam or for policymakers aiming to support the country's economic development.
- Text Content: [IMAGE ANALYSIS]
The image is a slide from a presentation, likely related to economic or statistical data. The slide is titled "THỊ TRƯỜNG BÁN LẺ SỐI ĐỒNG VÀ GIẢU TIỀM NĂNG." The content is divided into two main sections: text and graphs.

### Text Section:
The text is in Vietnamese and provides a brief overview of Vietnam's economic situation. It mentions that Vietnam is the 16th largest economy in the world, with a population of 98.9 million people. The population is projected to reach 100 million by 2025. The slide also discusses the country's economic growth, noting that Vietnam's economy is expected to grow at a rate of 8.5% per year from 2017 to 2022. The text also mentions that the country's economy is expected to grow at a rate of 44.4% per year from 2017 to 2022.

### Graphs:
The slide includes two bar graphs. The first graph shows the growth in the number of people in Vietnam from 2017 to 2022. The second graph shows the growth in the number of people in other countries from 2017 to 2022.

#### First Graph:
- **Title:** "Tăng trưởng thu nhập bình quân đầu người giai đoạn 2017-2022"
- **X-Axis:** Countries
- **Y-Axis:** Percentage
- **Bars:** Each country's percentage growth in the number of people from 2017 to 2022.

#### Second Graph:
- **Title:** "Doanh số bán lẻ hàng hóa Việt Nam"
- **X-Axis:** Years
- **Y-Axis:** Percentage
- **Bars:** Each year's percentage growth in the number of people in Vietnam.

### Analysis:
The first graph shows that Vietnam's population growth is expected to be the highest among the listed countries, with a growth rate of 8.5% per year from 2017 to 2022. This indicates a significant population increase in Vietnam during this period.

The second graph shows that Vietnam's population growth is expected to be the lowest among the listed countries, with a growth rate of 2.5% per year from 2017 to 2022. This indicates a slower population increase in Vietnam during this period.

### Conclusion:
The slide provides a comparative analysis of Vietnam's population growth with other countries, highlighting the significant population increase in Vietnam and the slower population growth in Vietnam. This information could be useful for understanding the demographic trends in Vietnam and for policymakers to consider the implications of these trends on economic growth and development.


Page 6 Visual Data:
- Description: [IMAGE ANALYSIS]
This image is a comprehensive infographic that provides insights into the growth and development of the Vietnamese economy, particularly in the context of technology and innovation. The infographic is divided into two main sections: a bar chart and a text-based section.

### Bar Chart
The bar chart compares the growth of technology and innovation in Vietnam from 2020 to 2030. The x-axis represents the years, while the y-axis represents the rank of countries in the top 20 technology and innovation leaders. The data is presented in a table format, with each country's rank and change in rank over the years.

#### Key Points:
1. **Vietnam's Position:**
   - In 2020, Vietnam is ranked 19th.
   - By 2030, Vietnam is projected to be ranked 12th.

2. **Growth Trends:**
   - Vietnam's rank has increased by 8 positions from 19th in 2020 to 12th in 2030.
   - The country's growth rate is projected to be 12.05% per annum, which is higher than the global average.

3. **Top 20 Countries:**
   - The top 20 countries in terms of technology and innovation are:
     - China
     - India
     - United States
     - Russia
     - Japan
     - Indonesia
     - Brazil
     - Pakistan
     - Egypt
     - Mexico
     - Germany
     - United Kingdom
     - France
     - Turkey
     - Pakistan
     - Italy
     - Thailand
     - South Korea
     - Spain
     - Nigeria
     - Philippines
     - Iran
     - Poland
     - Canada
     - Ukraine
     - Iraq

4. **Comparison with Other Countries:**
   - Vietnam's growth rate is projected to be higher than that of many other countries, including China, India, and the United States.

### Text-Based Section
The text-based section provides additional context and analysis of the data. It mentions that the World Data Lab's study predicts that Vietnam will see a significant increase in technology and innovation, with a projected GDP growth rate of 12.05% from 2023 to 2028. This growth rate is higher than the global average and is attributed to the country's strategic focus on technology and innovation.

The text also highlights that Vietnam's growth in technology and innovation is expected to be driven by several factors, including:
- **Innovation-driven growth:** Vietnam is expected to see a significant increase in innovation-driven growth, driven by the country's strong research and development efforts.
- **Globalization:** Vietnam is expected to benefit from globalization, with increased trade and investment opportunities.
- **Policy Support:** The government is expected to provide significant policy support to drive the growth in technology and innovation.

### Conclusion
This infographic provides a clear and concise overview of Vietnam's projected growth in technology and innovation, highlighting its potential to become a major player in the global technology landscape. The data is sourced from reputable organizations, such as World Data Lab and Mordor Intelligence, and is presented in a visually appealing manner to make the information accessible and engaging.
- Text Content: [IMAGE ANALYSIS]
The image is a presentation slide with a title in Vietnamese and a subtitle in English. The slide is divided into two main sections: a graph and a text block.

### Title Section:
- **Title**: "THỊ TRƯỜNG BÁN LẺ SỐI ĐỒNG VÀ GIẢU TIỀM NĂNG"
- **Subtitle**: "Tốc độ tăng trưởng nhanh bậc nhất trong khu vực"

### Graph Section:
- **X-Axis**: Represents the years 2020 and 2030.
- **Y-Axis**: Represents the rank of countries.
- **Data Points**: Each country is represented by a dot, and the dots are connected by lines to show the change in rank over the years.
- **Colors**: Different colors are used for each country, with some countries having multiple dots to indicate multiple years.

### Text Block Section:
- **Text**:
  - **Viet Nam được dự báo sẽ nằm trong top 20 thị trường tiêu dùng lớn nhất thế giới vào cuối thập kỷ 2020."
  - **World Data Lab's dự báo Việt Nam sẽ tăng 8 bậc trong top 30 thị trường tiêu dùng lớn nhất thế giới trong thập kỷ 2020 và sẽ chiếm 1.1% dân số thị trường tiêu dùng lớn nhất thế giới vào năm 2030."
  - **Còn theo nghiên cứu của Mordor Intelligence, thị trường bán lẻ Việt Nam được dự báo sẽ chứng kiến tốc độ tăng trưởng CAGR giai đoạn 2023-2028 đạt 12.05%, gấp khoảng 2 lần tốc độ tăng trưởng GDP trong cùng giai đoạn. Tốc độ tăng trưởng của ngành bán lẻ Việt Nam trong 5 năm tới vượt xa so với các thị trường Đông Á, Đông Nam Á và mức tăng trưởng bình quân của thị trường."
  - **Tốc độ tăng trưởng kép ngành bán lẻ GD 2023-2028**
    - **Viet Nam**: 12.05%
    - **Trung Quốc**: 10.00%
    - **Malaysia**: 5.94%
    - **Thái Lan**: 5.50%
    - **Indonesia**: 5.00%
    - **Hàn Quốc**: 4.58%
    - **Thế giới**: 4.50%
    - **Philippines**: 4.00%
    - **Đài Loan**: 4.00%
    - **Singapore**: 3.00%

### Footer Section:
- **Source**: "Nguồn: World Data Lab's, Mordor Intelligence"

### Analysis:
The slide presents data on the growth of the Vietnamese market in terms of sales and consumption. It shows that Vietnam is expected to be among the top 20 markets for consumer goods by the end of the decade. The data is sourced from World Data Lab and Mordor Intelligence, indicating the credibility and reliability of the data presented.

### Conclusion:
The slide highlights the significant growth potential of the Vietnamese market, particularly in terms of consumer goods, with a projected CAGR of 12.05% from 2023 to 2028. This growth is expected to be faster than the global average, making Vietnam a promising market for businesses looking to expand their operations in the region.


Page 7 Visual Data:
- Description: [IMAGE ANALYSIS]
This image is a marketing infographic that provides insights into the growth of e-commerce in Vietnam and the top 10 countries with the fastest growth in the e-commerce market. The infographic is divided into two main sections: a textual description and a bar chart.

### Textual Description
The textual description explains the growth of e-commerce in Vietnam and the top 10 countries with the fastest growth in the e-commerce market. It highlights the increasing reliance on technology and the impact of COVID-19 on e-commerce. The text also mentions that Vietnam is one of the fastest-growing e-commerce markets in the world, with a CAGR (Compound Annual Growth Rate) of 12.3% from 2023 to 2027.

### Bar Chart
The bar chart on the right side of the infographic shows the top 10 countries with the fastest growth in e-commerce from 2015 to 2022. The countries are listed in descending order of growth rate, with India leading at 14.11%, followed by Brazil at 14.07%, and Argentina at 13.63%. The chart also includes a legend to distinguish between the three types of transactions: traditional, e-commerce, and TMDT (traditional + digital).

### Key Points
1. **Vietnam's Growth**: Vietnam is one of the fastest-growing e-commerce markets in the world, with a CAGR of 12.3% from 2023 to 2027.
2. **Top 10 Countries**: India, Brazil, and Argentina are among the top 10 countries with the fastest growth in e-commerce.
3. **Technological Impact**: The growth in e-commerce is attributed to the increasing reliance on technology and the impact of COVID-19 on consumer behavior.
4. **CAGR Analysis**: The CAGR for Vietnam is 12.3%, which is higher than the global average of 12.3%.
5. **E-commerce Growth**: The top 10 countries with the fastest growth in e-commerce are India, Brazil, Argentina, Turkey, Mexico, Russia, Vietnam, China, South Africa, and Italy.

### Conclusion
This infographic provides valuable insights into the growth of e-commerce in Vietnam and the global trends driving it. It highlights the importance of technology and the impact of COVID-19 on consumer behavior, making it a useful resource for businesses looking to expand their e-commerce operations in Vietnam.
- Text Content: [IMAGE ANALYSIS]
The image is a slide from a presentation, likely related to market trends or economic data. The slide is divided into two main sections: text and bar chart.

### Text Section
The text section is written in Vietnamese and discusses the impact of technology and e-commerce on the Vietnamese market. It mentions that the Vietnamese market is experiencing rapid growth in e-commerce due to the spread of technology and the COVID-19 pandemic. The slide highlights that Vietnam is one of the top ten countries in terms of e-commerce growth, with a CAGR (Compound Annual Growth Rate) of 12.3% from 2023 to 2027.

### Bar Chart Section
The bar chart on the right side of the slide shows the top 10 countries in terms of e-commerce growth from 2015 to 2022. The countries are listed in descending order of growth rate. The growth rate is calculated using the compound annual growth rate (CAGR) method. The data is sourced from Kantar, Ecommerce DB, Statista, and PSI.

#### Top 10 Countries in Terms of E-commerce Growth (CAGR 2023-2027)
| Country | CAGR |
|---------|-----|
| India   | 14.11|
| Brazil  | 14.07|
| Argentina| 13.63|
| Turkey  | 13.57|
| Mexico  | 12.93|
| Russia  | 12.78|
| Vietnam | 12.3  |
| China   | 12.17|
| South Africa| 11.89|
| Italy   | 11.59|

### Analysis
The bar chart shows that Vietnam has the highest growth rate in e-commerce among the listed countries, with a CAGR of 12.3% from 2023 to 2027. This indicates that Vietnam is experiencing significant growth in e-commerce, which is driven by the spread of technology and the COVID-19 pandemic. The other countries listed have growth rates ranging from 12.17% to 14.11%, with Brazil and India having the highest growth rates.

### Conclusion
The slide provides a clear and concise overview of the Vietnamese e-commerce market's growth trends, highlighting Vietnam's leadership in the top 10 countries in terms of e-commerce growth. The data sources used for the analysis are reputable and provide a reliable source of information.


Page 8 Visual Data:
- Description: [IMAGE ANALYSIS]
This image appears to be a slide from a presentation, likely discussing the market share and growth of various retail chains in Vietnam. The slide is titled "Những 'Tay Chơi' lớn trên thị trường bán lẻ" which translates to "Some 'Chips' that are Large on the Retail Market."

### Key Points on the Slide:

1. **Introduction**:
   - The slide starts with a brief introduction to retail in Vietnam, highlighting the importance of retail chains in the market.

2. **Market Share Analysis**:
   - There is a bar chart that shows the total sales of various retail chains in Vietnam.
   - The chart includes the following retail chains:
     - Vincom (1,747 m2)
     - Central Retail (1,200 m2)
     - Aeon (1,040 m2)
     - Lotte Retail (253 m2)

3. **Chain Comparison**:
   - The chart compares the total sales of these chains.
   - Vincom has the highest sales, followed by Central Retail, Aeon, and Lotte Retail.

4. **Chain Growth**:
   - The slide mentions that the growth of these chains is significant.
   - Vincom, Central Retail, and Aeon have shown strong growth in recent years.

5. **Chain Strategy**:
   - The slide discusses the strategies of these chains.
   - Vincom, Central Retail, and Aeon are known for their strategic growth and expansion plans.

### Additional Information:
- The slide also includes a paragraph that discusses the growth of retail chains in Vietnam.
- It mentions that Vincom, Central Retail, and Aeon are expected to continue growing in the future.
- The slide also includes a reference to the "PSI tổng hợp và ưu tiên" which translates to "Total Summary and Priorities."

### Conclusion:
This slide provides a comprehensive overview of the retail market in Vietnam, focusing on the growth and strategies of major retail chains. The bar chart and the accompanying text provide clear insights into the market dynamics and future prospects of these chains.
- Text Content: [IMAGE ANALYSIS]
The image is a page from a document, likely a report or analysis, focusing on retail market trends in Vietnam. The layout is divided into several sections:

1. **Header Section**:
   - The header contains the title in bold, "Những 'Tay Chơi' Lớn Trên Thị Trường Bán Lẻ," which translates to "Some Big Players in the Retail Market."

2. **Main Body Section**:
   - The main body contains a paragraph discussing the growth of retail in Vietnam, mentioning specific companies such as Vincom, Central Retail, Aeon, and Lotte Retail.
   - There is a bar graph on the right side of the page, showing the total sales of these companies in square meters (m²).

3. **Graph Section**:
   - The bar graph is divided into four bars, each representing a different company:
     - Vincom: 1,747 m²
     - Central Retail: 1,200 m²
     - Aeon: 1,040 m²
     - Lotte Retail: 253 m²

4. **Additional Text**:
   - Below the graph, there is a paragraph explaining the growth of retail in Vietnam and the role of these companies in the market.
   - The paragraph mentions that the growth of retail in Vietnam is driven by the expansion of large-scale retail chains such as Vincom, Central Retail, Aeon, and Lotte Retail.

5. **Footer Section**:
   - The footer contains the source of the data, "PSI tổng hợp và quốc tế."

The layout is clear and organized, with the main body providing the most detailed information, while the graph and additional text provide supplementary insights. The use of bold text and clear headings helps in organizing the content effectively.


Page 9 Visual Data:
- Description: [IMAGE ANALYSIS]
This image is a marketing presentation slide titled "NGÀNH HÀNG NỘI BẤT" (Niche Market). The slide is divided into two main sections: "Hàng tiêu dùng nhanh" (Fast-moving consumer goods) and "Top mặt hàng tăng trưởng nhanh nhất trên kênh phân phối trực tuyến 2022 (%YoY)" (Top-selling products with the fastest growth on the e-commerce channel in 2022 (%YoY)).

### Fast-moving consumer goods (Hàng tiêu dùng nhanh)

#### Text Description

The text on the left side of the slide provides a brief overview of the top-selling products in Vietnam. The products listed are:
1. Kem chong nang (Kem chong nang)
2. Chăm sóc tay và cơ thể (Hand and body care)
3. Nước giải (Body wash)
4. Thức uống không cồn (Non-alcohol drink)
5. Sữa bột (Dairy products)

#### Bar Chart

The bar chart on the right side of the slide shows the percentage YoY growth for each product category. The top-selling products are:
1. Kem chong nang (Kem chong nang) - 84.2%
2. Chăm sóc tay và cơ thể (Hand and body care) - 82.2%
3. Nước giải (Body wash) - 62%
4. Thức uống không cồn (Non-alcohol drink) - 53.7%
5. Sữa bột (Dairy products) - 51%

### Business Analysis

The slide highlights the top-selling products in Vietnam, indicating that hand and body care products, non-alcohol drinks, and dairy products are the most popular among consumers. The growth rates for these products are also quite high, suggesting strong demand and potential for further growth in the e-commerce market.

### Conclusion

This slide is a valuable resource for businesses looking to understand the current trends and popular products in the Vietnamese market. By focusing on these top-selling items, businesses can target their marketing efforts more effectively and capitalize on the growing demand for these products.
- Text Content: [IMAGE ANALYSIS]
The image is a page from a document, likely a report or analysis, focusing on the "NGÀNH HÀNG NỘI BẤT" (Industry). The layout is divided into two main sections: a textual section and a graphical section.

### Textual Section:
The textual section contains a paragraph of text in Vietnamese, which translates to:
"Thị trường bán lẻ hàng tiêu dùng ở Việt Nam được thông qua các nhà bán lẻ như Aeon, Lotte Mart, Saigon Co-op, Winmart và Bach hoa xanh. Tăng trưởng nhanh hàng tiêu dùng chủ yếu phụ thuộc vào tăng trưởng của ngành hàng không thể thiếu. Trong đó, các mặt hàng chung kiến tăng trưởng nhanh nhất là thức uống không cồn và chăm sóc cá nhân, đặc biệt là thông qua kênh phân phối trực tiếp."

Translated to English:
"The retail market for consumer goods in Vietnam is driven by various retailers such as Aeon, Lotte Mart, Saigon Co-op, Winmart, and Bach hoa xanh. Growth in consumer goods is mainly driven by the growth of the non-food sector. Among the fastest-growing categories are non-alcoholic beverages and personal care, particularly through direct distribution channels."

### Graphical Section:
The graphical section presents a bar chart titled "Top mặt hàng tăng trưởng nhanh nhất trên kênh phân phối trực tiếp 2022 (%YoY)" (The fastest-growing categories on direct distribution channels in 2022 (%YoY)). The chart includes five categories:
1. Kem chong nang (Non-alcoholic beverages)
2. Chăm sóc tay và cơ thể (Personal care)
3. Nước giải khát (Non-alcoholic beverages)
4. Thức uống không cồn (Non-alcoholic beverages)
5. Sữa bột (Dairy products)

Each category is represented by a horizontal bar, with the length of the bar indicating the percentage of growth compared to the previous year (%YoY). The bars are color-coded as follows:
- Light blue for Kem chong nang (Non-alcoholic beverages)
- Dark blue for Chăm sóc tay và cơ thể (Personal care)
- Light grey for Nước giải khát (Non-alcoholic beverages)
- Light blue for Thức uống không cồn (Non-alcoholic beverages)
- Light blue for Sữa bột (Dairy products)

### Analysis:
The bar chart shows that the fastest-growing categories on direct distribution channels in 2022 are:
1. Non-alcoholic beverages (Kem chong nang)
2. Personal care (Chăm sóc tay và cơ thể)
3. Non-alcoholic beverages (Nước giải khát)
4. Non-alcoholic beverages (Thức uống không cồn)
5. Dairy products (Sữa bột)

This indicates that the retail market for consumer goods in Vietnam is dominated by these categories, with non-alcoholic beverages and personal care being the most rapidly growing sectors.


Page 10 Visual Data:
- Description: [IMAGE ANALYSIS]
This image appears to be a slide from a presentation, likely related to the technology sector, specifically focusing on the growth and performance of certain industries. The slide is divided into two main sections: a textual section and a graphical section.

### Textual Section:
The textual section contains a paragraph of text in Vietnamese, which discusses the current state of the technology sector in Vietnam. The text mentions that the technology industry has seen significant growth in recent years, with a focus on the top three companies: Apple, Samsung, and others. The text also highlights the challenges faced by the industry, such as the impact of the COVID-19 pandemic and the need for continuous innovation to stay competitive.

### Graphical Section:
The graphical section consists of two main graphs. The left graph is a bar chart, which shows the growth in revenue or some other metric for three different companies: MWG, FRT, and DGW. The bars are color-coded and represent different time periods: June 2022, September 2022, December 2022, and March 2023. The bars are colored in blue, gray, and black, respectively.

The right graph is a line graph, which shows the revenue or some other metric for the same three companies over time. The line graph is color-coded and represents the same time periods as the bar chart. The line graph shows fluctuations in revenue over the years, with some periods of growth and others of decline.

### Additional Information:
- **Source**: The slide is attributed to "PSI tổng hợp và tính toán" (PSI total compilation and calculation).
- **Color Scheme**: The slide uses a color scheme of blue, gray, and black, which is consistent throughout the presentation.

### Analysis:
The slide provides a comprehensive overview of the technology sector in Vietnam, highlighting the growth and challenges faced by the industry. The bar chart and line graph together provide a visual representation of the revenue or other metrics for the three companies over time, allowing for a clear understanding of the trends and fluctuations.

### Marketing Post:
Using the information from the slide, a marketing post could focus on the following points:
1. **Industry Growth**: Highlight the significant growth in the technology sector in Vietnam, emphasizing the top three companies.
2. **Challenges and Opportunities**: Discuss the challenges faced by the industry, such as the impact of the COVID-19 pandemic, and opportunities for continued innovation.
3. **Performance Analysis**: Provide a detailed analysis of the revenue or other metrics for the three companies over time, using both the bar chart and line graph.
4. **Future Outlook**: Conclude with a prediction or outlook for the industry, based on the trends observed.

By providing this detailed description, a marketing post can effectively communicate the key points of the slide and engage the audience with the information presented.
- Text Content: [IMAGE ANALYSIS]
The image is a page from a document, likely a report or analysis, focusing on the "NGÀNH HÀNG NỘI BẤT" (Industry). The layout is divided into two main sections: text and charts.

### Text Section:
The text is written in Vietnamese and discusses the current state of the construction and real estate industry. It mentions that the construction industry has seen a significant increase in activity, with a peak in the third quarter of 2022. The industry is heavily reliant on the construction of high-rise buildings, particularly those by Apple and Samsung. The text also highlights the challenges faced by the industry, such as supply chain disruptions and the impact of the COVID-19 pandemic.

### Charts:
The charts on the page are color-coded and represent different metrics:
1. **Bar Chart:**
   - **X-axis:** Represents different categories (MWG, FRT, DGW).
   - **Y-axis:** Represents the percentage of the metric.
   - **Bars:** Represent the percentage of each category.
   - **Colors:** MWG is in blue, FRT is in light blue, and DGW is in dark blue.

2. **Line Chart:**
   - **X-axis:** Represents the months from March 2020 to June 2023.
   - **Y-axis:** Represents the percentage of the metric.
   - **Lines:** Represent the percentage change over time for each category.
   - **Colors:** MWG is in orange, FRT is in yellow, and DGW is in light green.

### Analysis:
- **MWG (Medium-Value Group):** This category shows a significant increase in the percentage of the metric from March 2020 to June 2023.
- **FRT (Fast-Response Time):** This category shows a decrease in the percentage of the metric from March 2020 to June 2023.
- **DGW (Delayed-Response Time):** This category shows a fluctuating trend with a decrease in the percentage of the metric from March 2020 to June 2023.

### Conclusion:
The text and charts together provide a comprehensive overview of the construction and real estate industry's performance over the specified period. The bar chart highlights the overall trend, while the line chart provides a more detailed view of the changes over time. This information can be used to understand the industry's performance, identify trends, and make informed decisions.


Page 1 Visual Data:
- Description: [IMAGE ANALYSIS]
This image is a page from a scholarly article titled "Acceptance of AI technology in retail: The case of Generation Z and Generation Y." The article is authored by Bùi Ngọc Tuấn Anh, Nguyễn Thiện Thy, Cao Thị Lan Anh, Phạm Ngọc Hải Yến, Nguyễn Duong Danh, and Trần Việt Hảo. The authors are affiliated with the Mô Thanh phố Hồ Chí Minh, Thành phố Hồ Chí Minh, Việt Nam.

The page contains several sections, including the title, authors, abstract, keywords, and a table of contents. The abstract provides an overview of the study's main findings and methodology. The keywords section lists terms related to the study, such as "personalization," "retail AI technology acceptance," "privacy concerns," and "self-efficacy."

The table of contents is organized in a clear and concise manner, with entries such as "Introduction," "Literature Review," "Methodology," "Results," and "Conclusion." The table of contents helps readers navigate the article efficiently and understand the structure of the research.

Overall, this page provides a comprehensive overview of the article's content, making it easy for readers to understand the research objectives, methodology, and findings.
- Text Content: [IMAGE ANALYSIS]
The image is a page from a scholarly article, specifically from a journal titled "Bui Ngoc Tuân Anh và công sự. HCMCOUJS-Kinh tế và Quản trị kinh doanh, 20(6), 52-67." The page number is 52. The title of the article is "Acceptance of AI technology in retail: The case of Generation Z and Generation Y." The authors of the article are Bùi Ngọc Tuấn Anh, Nguyễn Thiện Thỳ, Cao Thị Lan Anh, Phạm Ngọc Hải Yến, Nguyễn Duong Danh, and Trần Việt Hạo. The authors are affiliated with the Mô Thanh phố Hồ Chí Minh, Thành phố Hồ Chí Minh, Việt Nam.

The page contains the following sections:

1. **Title and Authors**: The title of the article is "Acceptance of AI technology in retail: The case of Generation Z and Generation Y." The authors are listed in the order of their names, with the last name followed by an asterisk (*).

2. **Abstract**: The abstract of the article is as follows:
   - "In recent years, technology applications in the retail industry have grown and generated significant value to the businesses and customers. While enhancing customers' experiences by personalizing needs, the technology in the retail industry is also facing various risks, especially privacy concerns. This study investigates the impact of privacy concerns through the Social Contract Theory, also combining the Technology Acceptance Model to evaluate behavioral intention towards Self-Services Technology (SST) integrated AI at retail stores. The survey received 250 responses from Gen Z and Gen Y in Ho Chi Minh City, using Smart PLS 4 to evaluate the data. The results show a forceful impact of the perceived ease of use and the perceived usefulness on behavioral intention. Privacy concerns are not the factor causing the negative effect on behavioral intention. This understanding will contribute to the theoretical aspect and the practical implications for the administrators when using the new technology to augment the users' experiences in purchasing."

3. **Keywords**: The keywords listed are:
   - Personalization
   - Retail AI technology acceptance
   - Privacy concerns
   - Self-efficacy

The layout is typical of academic articles, with clear sections for the title, authors, abstract, and keywords. The page is formatted with a standard layout for academic journals, including the page number, author names, and the title of the article.


Page 4 Visual Data:
- Description: [IMAGE ANALYSIS]
This image appears to be a page from a book or academic paper, specifically page 55 of a document titled "Bùi Ngọc Tuấn Anh và công sự. HCMCOUJS-Kinh tế và Quản trị kinh doanh, 20(6), 52-67." The page contains text in Vietnamese, discussing various topics related to business and management. The content is structured into sections, with headings and subheadings indicating different topics or sections of the document. The text is well-organized, with paragraphs and bullet points, making it easy to read and understand the content. The page number at the top right corner indicates that this is part of a larger document, likely a research paper or academic article. The overall layout and formatting suggest that this is a professional or academic document, possibly intended for readers with a background in business or management.
- Text Content: [IMAGE ANALYSIS]
The image is a page from a document, specifically from a section titled "Bùi Ngọc Tuấn Anh và công sự." The document appears to be discussing the impact of technology on the economy and society, focusing on the role of technology in various industries and the impact on employment and economic growth. The page number is 55.

The content of the page is as follows:

---

**Bùi Ngọc Tuấn Anh và công sự. HCMCOUJS-Kinh tế và Quản trị kinh doanh, 20(6), 52-67**

**2.3. Các khái niệm liên quan**

**2.3.1. Cả nhân hóa**

Cả nhân hóa là việc sử dụng thông tin cá nhân của người tiêu dùng để tạo ra trải nghiệm mua sắm độc đáo, đáp ứng nhu cầu và sở thích của họ (Aksoy & ctg., 2023). Trong các ngành hàng bán lẻ trực tuyến như Amazon Go, cả nhân hóa được thực hiện qua việc thu thập và phân tích dữ liệu liên quan đến người tiêu dùng, điều chỉnh sản phẩm, giao dịch, và quy trình tương tác với khách hàng. Các ngành hàng khác như giỏ hàng ảo và thanh toán trực tuyến như ư hóa sử thị trường và đáp ứng kỳ vọng của khách hàng (Hoyer & ctg., 2020; Kumar & ctg., 2021). Việc sử dụng AI vào không gian bán lẻ giúp tạo môi trường tương tác dễ dàng, nâng cao hiệu quả mua sắm và xây dựng lòng trung thành khách hàng.

**2.3.2. Lo ngại về quyền riêng tư**

Baek và Morimoto (2012) định nghĩa lo ngại về quyền riêng tư là mức độ lo lắng về khả năng chém đâm quyền riêng tư và ngăn chặn việc tiếp cận thông tin cá nhân của người tiêu dùng cho người khác. Người tiêu dùng lo ngại về việc sử dụng thông tin cá nhân của họ có thể bị bẻ thư và người không được phép sử dụng cho mục đích không mong muốn, dẫn đến mất quyền riêng tư (Xu & ctg., 2011). Môi lo ngại đó có thể bao gồm việc tiếp cận thông tin từ các nhà bán lẻ cũng như việc tiếp cận thông tin từ các công ty (Wu & ctg., 2012). Nếu dữ liệu liên quan đến người tiêu dùng được thu thập và sử dụng không đúng cách, có thể gây ra sự mất mát từ thị trường (Baruh & ctg., 2017).

**2.3.3. Niềm tin vào năng lực bản thân**

Niềm tin vào năng lực bản thân là yếu tố quan trọng trong việc xây dựng niềm tin vào sự ổn định của người dùng. Niềm tin vào năng lực bản thân để đáp ứng các yêu cầu liên quan đến những vấn đề cá nhân và xã hội (Pramana, 2018). Trong bối cảnh SST, yếu tố này có thể giúp người dùng có sự ổn định trong việc sử dụng công nghệ và sự ổn định trong việc làm việc.

**2.4. Phát triển các giải thích**

**2.4.1. Ánh hướng của cả nhân hóa trong mô hình kinh doanh**

Cả nhân hóa ngày càng phổ biến và mang lại lợi ích cho cả doanh nghiệp và khách hàng. Tuy nhiên, điều này cũng tạo ra lo ngại về quyền riêng tư (Roussos & ctg., 2003), tạo ra "những lý do nhân hóa và quyền riêng tư" (Awad & Krishnan, 2006). Môi quan tâm về quyền riêng tư của người dùng tăng lên cùng với sự phát triển của Internet và công nghệ không dây (Swani & ctg., 2021), cho thấy người dùng đang dần nhận thức rõ các mối đe dọa đối với quyền riêng tư. Các ngành công cụ trung tâm ra ràng cả nhân hóa có thể ảnh hưởng đến quyền riêng tư với mục đích tác động khách hàng, tùy thuộc vào mức độ lo ngại của người tiêu dùng (Gouthier & ctg., 2022). Do đó, khi muốn triển khai các dịch vụ cả nhân hóa, người dùng sẽ cần cung cấp nhiều thông tin cá nhân, song lo ngại về quyền riêng tư cũng tăng lên.

**H1: Cả nhân hóa tác động thuận lợi đối với lo lắng quyền riêng tư**

Việc cả nhân hóa trong các ứng dụng số giúp người dùng có thể lựa chọn, sắp xếp cấu hình và phát triển trình bày thông tin một cách dễ dàng, từ đó giúp người dùng có thể tự quản lý và bảo vệ quyền riêng tư của họ.

---

The document discusses the impact of technology on various industries, including the role of technology in


Page 8 Visual Data:
- Description: [IMAGE ANALYSIS]
This image is a page from a research paper titled "Bùi Ngọc Tuấn Anh và công cụ HCMCOUJS-Kinh tế và Quản trị kinh doanh, 20(6), 52-67". The page contains a table with various data points related to different variables and their corresponding percentages. The table is divided into several columns and rows, with each cell containing numerical values and percentages. The table is structured in a way that makes it easy to compare different variables and their performance.

### Table Description:
- **Columns:**
  - **Kích thước mẫu:** This column lists the different variables being measured.
  - **250:** This column shows the percentage of the sample size for each variable.
  - **100%:** This column shows the percentage of the total sample size for each variable.

- **Rows:**
  - **Kích thước mẫu:** This row lists the different variables.
  - **250:** This row shows the percentage of the sample size for each variable.
  - **100%:** This row shows the percentage of the total sample size for each variable.

### Data Points:
- **Kích thước mẫu:**
  - **Phúc vụ/Nhân viên bán hàng:** 4%
  - **Công nhân/Nông dân/Lao động chăn tay:** 4%
  - **Học sinh/Sinh viên:** 168%
  - **Khác:** 3%

- **Thu nhập mỗi tháng:**
  - **Duôi 3,000,000 đồng:** 99%
  - **3,000,000 - 7,500,000 đồng:** 73%
  - **7,500,000 - 15,000,000 đồng:** 51%
  - **Trên 15,000,000 đồng:** 27%

- **Tân suất mua sắm tại các điểm bán lẻ:**
  - **Duôi 01 lần/tuần:** 53%
  - **01 - 02 lần/tuần:** 117%
  - **03 - 04 lần/tuần:** 55%
  - **Trên 05 lần/tuần:** 25%

### Analysis:
- **Kích thước mẫu:** The sample size for each variable ranges from 4% to 168%, indicating that the sample size is relatively small for some variables.
- **Thu nhập mỗi tháng:** The percentage of respondents earning between 3,000,000 and 7,500,000 dong is the highest at 73%, while the lowest percentage is for those earning between 7,500,000 and 15,000,000 dong (27%).
- **Tân suất mua sắm tại các điểm bán lẻ:** The percentage of respondents shopping at different retail outlets varies from 21.2% to 46.8%, with the highest percentage for those shopping once a week (53%) and the lowest for those shopping five times a week (25%).

### Conclusion:
The table provides valuable insights into the distribution of different variables within the sample. The small sample size for some variables suggests that the results may not be representative of the entire population. The data can be used to identify areas for improvement or further research.
- Text Content: [IMAGE ANALYSIS]
The image is a page from a document, specifically from a research paper. The page number is 59, and the title of the document is "Bùi Ngọc Tuấn Anh và công cụ HCMCOUJS-Kinh tế và Quản trị kinh doanh, 20(6), 52-67." The document appears to be discussing statistical analysis and research findings related to business and economics.

### Table Description:

#### Table Title:
- **Kích thước mẫu**
- **Thu nhập mỗi tháng**
- **Tân suất mua sắm tại các địa điểm bán lẻ**

### Table Content:
- **Kích thước mẫu**:
  - **250** and **100%**
  - **Phúc vụ/Nhân viên bán hàng**
  - **Công nhân/Nông dân/Lao động chăn tay**
  - **Học sinh/Sinh viên**
  - **Khác**

- **Thu nhập mỗi tháng**:
  - **Duôi 3,000,000 đồng**
  - **3,000,000 - dưới 7,500,000 đồng**
  - **7,500,000 - dưới 15,000,000 đồng**
  - **Trên 15,000,000 đồng**

- **Tân suất mua sắm tại các địa điểm bán lẻ**:
  - **Duôi 01 lần/tuần**
  - **01 - 02 lần/tuần**
  - **03 - 04 lần/tuần**
  - **Trên 05 lần/tuần**

### Analysis:
The table appears to be a part of a larger study, likely examining consumer behavior and purchasing patterns. The data is presented in a structured manner, with each column representing different variables and their respective values. The values are given in both 250 and 100% formats, which might indicate the sample size or the percentage of respondents.

### Relevant Knowledge:
- **Kích thước mẫu** refers to the sample size, which is crucial for statistical analysis. A larger sample size generally leads to more reliable results.
- **Thu nhập mỗi tháng** and **Tân suất mua sắm tại các địa điểm bán lẻ** are likely referring to income and shopping behavior, respectively. These variables are often used in economic studies to understand consumer spending patterns.
- **Phúc vụ/Nhân viên bán hàng**, **Công nhân/Nông dân/Lao động chăn tay**, **Học sinh/Sinh viên**, and **Khác** likely represent different job categories or demographic groups within the population being studied.

### Conclusion:
The table provides a snapshot of consumer behavior and purchasing patterns, which could be used to inform business strategies, marketing campaigns, and policy decisions. The structured format and detailed data make it a valuable resource for further analysis and interpretation.