Page 7 Visual Data:
- Description: [IMAGE ANALYSIS]
This image appears to be a page from a research paper or academic article, specifically from a journal titled "Kieu Anh Tai va cong su." The page number is 60. The content is in Vietnamese and discusses a study on the impact of various factors on the success of businesses in the HCMC (Ho Chi Minh City) region. The study focuses on the role of age, education, and other demographic variables in determining business success.

The text is structured into sections, with the main focus on the demographic variables and their impact on business success. The table on the page provides data on the distribution of business owners based on their age, education level, and other demographic factors. The data is presented in a clear and organized manner, with columns for the demographic variables and corresponding percentages of business owners.

The table includes columns for "Nam" (age), "Nữ" (female), "<25" (under 25 years old), "25-34" (25-34 years old), "35-44" (35-44 years old), "45-49" (45-49 years old), ">=50" (over 50 years old), "Duoi Phổ thông trung học" (primary education), "Phổ thông trung học" (secondary education), "Trung cấp cao đẳng" (higher education), and "Đại học trở lên" (higher education).

The data shows that the majority of business owners are between the ages of 25 and 44, with a significant number of women (female) and those with primary education. The table also includes percentages for each demographic group, indicating the proportion of business owners in each category.

Overall, the image provides a snapshot of the demographic distribution of business owners in the HCMC region, highlighting the importance of demographic factors in determining business success. This information could be useful for businesses looking to understand their target market and make informed decisions about their marketing strategies.
- Text Content: [IMAGE ANALYSIS]
The image is a page from a document, specifically from a research paper. 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 document appears to be discussing economic and business strategies, specifically focusing on the role of financial institutions in the Vietnamese economy.

The content of the page is as follows:

---

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

**4. Kết quả nghiên cứu và thảo luận**

**4.1. Mô tả mẫu**

Bảng 1 mô tả mẫu khảo sát gồm 386 trả lời lê.

**Bảng 1**

**Mô tả Mẫu**

| Tên số | Tỷ lệ |
|--------|--------|
| Giới tính | Nam | 40.2% |
| Giới tính | Nữ | 59.8% |
| < 25 | 8.3% | 45.9% |
| 25 - 34 | 16.1% | 45.9% |
| 35 - 44 | 16.1% | 18.1% |
| 45 - 49 | 11.7% | 18.1% |
| > 50 | 8.8% | 11.7% |
| Duôi Phổ thông trung học | 8.8% | 18.4% |
| Phổ thông trung học | 18.4% | 18.4% |
| Trung cấp học cao đẳng nghề | 16.8% | 16.8% |
| Đại học trung cấp | 56.0% | 56.0% |
| Mức doanh thu trung bình của các hàng (trích dẫn) | < 50 | 42.2% |
| 50 - < 100 | 36.3% |

---

**Description and Analysis**

The page presents a detailed breakdown of a research sample, which consists of 386 respondents. The sample is divided into various demographic categories, including gender, age, education level, and income. The data is presented in a table format, with each row representing a different demographic category and the corresponding percentage of respondents.

The table includes the following categories:
1. **Gender**
   - Male (Nam) - 40.2%
   - Female (Nữ) - 59.8%
2. **Age**
   - < 25 - 8.3%
   - 25 - 34 - 45.9%
   - 35 - 44 - 16.1%
   - 45 - 49 - 18.1%
   - > 50 - 8.8%
3. **Education Level**
   - Phổ thông trung học - 8.8%
   - Phổ thông trung học - 18.4%
   - Trung cấp học cao đẳng nghề - 16.8%
   - Đại học trung cấp - 56.0%
4. **Income**
   - < 50 - 42.2%
   - 50 - < 100 - 36.3%

The data is organized in a clear and structured manner, making it easy to interpret and analyze. The table provides insights into the demographic characteristics of the sample, which can be useful for further research and analysis.

---

**Answer to the Question:**

Based on the provided data, the demographic characteristics of the sample are as follows:
- **Gender**: 40.2% are male and 59.8% are female.
- **Age**: The majority (45.9%) are between the ages of 25 and 34, followed by 16.1% between 35 and 44, and 8.8% between 45 and 49.
- **Education Level**: The majority (56.0%) have completed a Phổ thông trung học, followed by Phổ thông trung học (18.4%), Trung cấp học cao đẳng nghề (16.8%), and Đại học trung cấp (56.0%).
- **Income**: The majority (42.2%) have a monthly income of < 50, while 36.3% have a monthly income of 50 - < 100.

This detailed


Page 8 Visual Data:
- Description: [IMAGE ANALYSIS]
This image is a table from a research paper titled "Kieu Anh Tai va cong su." The table is titled "4.2. Danh gia thang do" which translates to "Price Analysis." The table provides data on various economic indicators and their percentages. Here is a detailed description of the table:

| Tên số | Tỷ lệ |
|--------|--------|
| 100 - <200 | 14.0% |
| 200 - <500 | 4.9% |
| >= 500 | 2.6% |
| < 02 | 25.9% |
| 02 - <05 | 35.5% |
| 05 - <10 | 19.9% |
| 10 - <15 | 10.9% |
| >= 15 | 7.8% |
| < 5 | 6.5% |
| 5 - <30 | 21.8% |
| Quy mô của hàng (m2) | 57.5% |
| 30 - <60 | 57.5% |
| 60 - <100 | 8.8% |
| >= 100 | 5.4% |
| 01 | 28.2% |
| 02 | 33.4% |
| 03 | 18.1% |
| 04 | 13.0% |
| 05 | 7.3% |
| Tập hóa | 31.9% |
| Quản ấn, giải khát | 26.2% |
| Thời trang, mỹ phẩm & phụ kiện | 10.4% |
| Điện tử, đồ gia dụng & nội thất | 9.1% |
| Lương thực, thực phẩm | 6.5% |
| Thế thao, giải trí & du lịch | 2.6% |
| Thuốc, sức khỏe & thú cưng | 4.9% |
| Mẹ & bé | 5.7% |
| Khác (Ghi rõ) | 2.8% |
| Chi Online (Bán hàng trực tuyến) | 22.8% |
| Chi Offline (Bán hàng truyền thống) | 22.3% |
| Kết hợp Online và Offline | 54.9% |
| Tổng cộng mầu hợp lệ | 100% |

The table provides data on various economic indicators such as the number of businesses, the percentage of businesses with different sizes, the percentage of businesses with different numbers of employees, and the percentage of businesses with different types of businesses. The data is presented in a clear and organized manner, making it easy to understand the distribution of businesses across different categories.

This table can be used by marketers to understand the distribution of businesses in a specific market or industry, which can help in targeting specific segments and developing marketing strategies. The data can also be used to identify areas for improvement or expansion in the business sector.
- Text Content: [IMAGE ANALYSIS]
The image is a table with data from a study or report. The table is structured with two main columns: "Tân số" (new cases) and "Tỷ lệ" (percentage). The rows are divided into several categories, each with a specific range of values and corresponding percentages. Here is a detailed description of the table:

### Table Description:
- **Title**: The title at the top of the table is "Kiều Anh Tài và công sự. HCMCOUJS-Kinh tế và Quản trị Kinh doanh, 20(10), 54-70" which translates to "Interviews and Studies. HCMCOUJS - Business and Management, 20(10), 54-70".
- **Column Headers**: The table has two main columns: "Tân số" (new cases) and "Tỷ lệ" (percentage).
- **Rows**: The table has several rows, each representing a different category of data.
- **Data Categories**:
  - **100 - <200**: 54 cases, 14.0%.
  - **200 - <500**: 19 cases, 4.9%.
  - **>= 500**: 10 cases, 2.6%.
  - **< 02**: 100 cases, 25.9%.
  - **02 - <05**: 137 cases, 35.5%.
  - **05 - <10**: 77 cases, 19.9%.
  - **10 - <15**: 42 cases, 10.9%.
  - **>= 15**: 30 cases, 7.8%.
  - **< 5**: 25 cases, 6.5%.
  - **5 - <30**: 84 cases, 21.8%.
  - **Quy mô của hàng (m²)**: 222 cases, 57.5%.
  - **01**: 109 cases, 28.2%.
  - **02**: 129 cases, 33.4%.
  - **03**: 70 cases, 18.1%.
  - **04**: 50 cases, 13.0%.
  - **05**: 28 cases, 7.3%.
  - **Tập hóa**: 123 cases, 31.9%.
  - **Quản ấn, giải khát**: 101 cases, 26.2%.
  - **Thời trang, mỹ phẩm & phụ kiện**: 40 cases, 10.4%.
  - **Điện tử, đồ gia dụng & nội thất**: 35 cases, 9.1%.
  - **Lương thực, thực phẩm**: 25 cases, 6.5%.
  - **Thế thao, giải trí & du lịch**: 10 cases, 2.6%.
  - **Thú cưng, sức khỏe & thú cưng**: 19 cases, 4.9%.
  - **Mẹ & bé**: 22 cases, 5.7%.
  - **Khác (Ghi rõ)**: 11 cases, 2.8%.
  - **Chi Online (Bán hàng trực tuyến)**: 88 cases, 22.8%.
  - **Chi Offline (Bán hàng truyền thống)**: 86 cases, 22.3%.
  - **Kết hợp Online và Offline**: 212 cases, 54.9%.
  - **Tổng cộng mâu họp lệ**: 386 cases, 100%.
- **Footer**: The footer contains a note in Vietnamese: "Ghi chú: Phần tích dữ liệu".

### Analysis:
The table presents data on new cases and their corresponding percentages across various categories. The categories include new cases in different ranges, types of businesses, and different types of products or services. The data is organized in a clear and structured manner, making it easy to interpret and analyze.

### Relevant Knowledge:
The data in the table can be used to understand the distribution of new cases across different categories, which can be useful for further analysis and decision-making. For example, businesses with more than 500 employees might have a higher percentage of new cases compared to those with fewer employees. Similarly, businesses with a larger number of employees might have a higher percentage of new cases compared to those with fewer employees.

### Conclusion:
This table provides valuable insights into the


Page 9 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 contains a table with data from a study on the relationship between different factors affecting the performance of enterprises and the impact of technology on these factors. The table is divided into two main sections:

1. **Section 2: The Impact of Technology on Performance (Section 2.1)**: This section contains data on the impact of technology on various performance metrics such as efficiency, productivity, and innovation. The table shows the correlation coefficients (CR) and average variance extracted (AVE) for each factor. For example, the correlation coefficient for efficiency (E) is 0.892, and the average variance extracted is 0.808.

2. **Section 3: The Impact of Technology on Performance (Section 3.1)**: This section provides data on the impact of technology on various performance metrics, including efficiency, productivity, and innovation. The table shows the correlation coefficients (CR) and average variance extracted (AVE) for each factor. For example, the correlation coefficient for efficiency (E) is 0.707, and the average variance extracted is 0.745.

The table is structured with columns for different performance metrics, including efficiency (E), productivity (P), innovation (I), and technology (T). The data is presented in a clear and organized manner, making it easy to understand the impact of technology on various performance metrics.
- Text Content: [IMAGE ANALYSIS]
The image is a page from a research paper, specifically from the journal "Kieu Anh Tai va cong su." The page number is 62. The paper appears to be discussing econometrics and business management, as indicated by the title and the references at the bottom. The content is structured into sections with headings and subheadings, and the text is in Vietnamese.

### Markdown Format:

```markdown
# Kieu Anh Tai va cong su. HCMCOUJS-Kinh te va Quan tri Kinh doanh, 20(10), 54-70

62

biên khác đề dán giá độ tin cậy và giá trị của các thành phần bậc thấp thuộc hai câu trúc của EO và PVDS (Sarstedt & ctb., 2020). Các nguồn chẩn nhận của độ tin cậy tổng hợp (CR) là 0.700 (Hair & ctb., 2019). Giá trị hội tụ được đánh giá thông qua hệ số tài nguyên lớn hơn 0.700 và phương sai trích (AVE) lớn hơn 0.50 (Hair & ctb., 2019). Hệ số HTMT được áp dụng để xem xét giá trị phân biệt (Henseler & ctb., 2015). Kết quả thể hiện trong Bảng 2 và Bảng 3 cho thấy các thành phần bậc thấp của EO và PVDS đều đạt các tiêu chí này.

## Bảng 2

## Kết Quả Độ Tin Cậy và Giá Trị Hội Tự (Nhân Tố Bác 1)

| Thành phần bậc 1 | Hệ số tài nguyên | Cronbach’s Alpha | CR | AVE |
|------------------|------------------|------------------|-----|-----|
| Định hướng doanh chúa (EO) | [0.892 - 0.906] | 0.881 | 0.927 | 0.808 |
| Định hướng đổi mới (EOI) | [0.896 - 0.916] | 0.889 | 0.931 | 0.818 |
| Định hướng chủ động (EOP) | [0.896 - 0.916] | 0.889 | 0.931 | 0.818 |
| Định hướng chấp nhận rủi ro (EOR) | [0.889 - 0.905] | 0.883 | 0.928 | 0.811 |

## Nhân thức giá trị phân biệt (PVDS)

| Giá trị chức năng (VFU) | [0.802 - 0.849] | 0.911 | 0.931 | 0.692 |
| Giá trị nhận thức (VEP) | [0.905 - 0.924] | 0.899 | 0.937 | 0.832 |
| Giá trị cảm xúc (VEM) | [0.902 - 0.936] | 0.909 | 0.943 | 0.845 |
| Giá trị xã hội (VSO) | [0.895 - 0.914] | 0.888 | 0.930 | 0.816 |
| Giá trị điều kiện (VCO) | [0.948 - 0.957] | 0.898 | 0.951 | 0.907 |

## Ghi chú: Phân tích dữ liệu

## Bảng 3

## Kết Quả Giá Trị Phân Biệt (Nhân Tố Bác 1) theo Hệ Số HTMT

| EOI | EOP | EOR | VCO | VEM | VEP | VFU |
|---|---|---|---|---|---|---|
| EOP | 0.707 |  |  |  |  |  |
| EOR |  | 0.693 |  |  |  |  |
| VCO |  |  | 0.136 |  |  |  |
| VEM |  |  |  | 0.115 |  |  |
| VEP |  |  |  |  | 0.084 |  |
| VFU |  |  |  |  |  | 0.164 |
| VSO


Page 10 Visual Data:
- Description: [IMAGE ANALYSIS]
This image is a page from a research paper titled "Kieu Anh Tai va cong su." The paper is about the impact of economic conditions and financial stability on the stock market. The table in the image is a part of the paper's results section, specifically focusing on the correlation between economic conditions and financial stability.

### Table Description:
The table is divided into two main sections:
1. **Bảng 4: Kết quả Đồ tin Cây và Giá trị Hồi Tự (Mô Hình Nghĩa Cưu)** (Table 4: Results of Stock Trees and Value of Return (Image Type))
2. **Bảng 5: Kết quả Giá trị Phân Biệt (Mô Hình Nghĩa Cưu) theo Hệ Số HTMT (Table 5: Results of Value Analysis (Image Type) according to HTMT System)

### Table Content:
- **Columns**: The table has several columns, each representing different variables or measures.
- **Rows**: There are multiple rows, each representing different combinations of variables.
- **Data**: The data in the table is presented in a structured format, with each row containing numerical values and possibly some text or notes.

### Example Data:
- **Bảng 4: Kết quả Đồ tin Cây và Giá trị Hồi Tự (Mô Hình Nghĩa Cưu)**:
  - **Columns**:
    - **Khái niệm**: Economic conditions and financial stability.
    - **Hệ số tài ngài**: Correlation coefficient.
    - **Cronbach Alpha**: Internal consistency reliability.
    - **CR**: Correlation coefficient.
    - **AVE**: Average variance extracted.
  - **Rows**:
    - **Định hướng doanh thu (EO)**: Economic conditions.
    - **Năng lực doanh thu (EC)**: Financial stability.
    - **Đối môi khám phá (ER)**: Economic conditions.
    - **Đối môi khai thác (ET)**: Financial stability.
    - **Áp lực cạnh tranh (CP)**: Economic conditions.
    - **Nhân thức giá trị dịch vụ sở hữu (PVDS)**: Financial stability.
    - **Số hóa (DG)**: Economic conditions.
    - **Dịch vụ hóa (ST)**: Financial stability.
  - **Ghi chú**: Phân tích dữ liệu.

- **Bảng 5: Kết quả Giá trị Phân Biệt (Mô Hình Nghĩa Cưu) theo Hệ Số HTMT**:
  - **Columns**:
    - **CP**: Correlation coefficient.
    - **DG**: Economic conditions.
    - **EC**: Financial stability.
    - **EO**: Economic conditions.
    - **ER**: Financial stability.
    - **ET**: Economic conditions.
    - **PVDS**: Financial stability.
    - **ST**: Economic conditions.
    - **PVDSxET**: Economic conditions.
    - **PVDSxER**: Financial stability.
    - **CPxET**: Correlation coefficient.
    - **CPxER**: Correlation coefficient.
  - **Rows**:
    - **DG**: 0.171
    - **EC**: 0.117
    - **EO**: 0.145
    - **ER**: 0.070
    - **ET**: 0.125
    - **PVDS**: 0.236
    - **ST**: 0.145
    - **PVDSxET**: 0.083
    - **PVDSxER**: 0.054
    - **CPxET**: 0.054
    - **CPxER**: 0.055

### Analysis:
- **Bảng 4**: This table shows the correlation between economic conditions (EO) and financial stability (EC) using the HTMT system. The correlation coefficient (CR) is 0.902, indicating a strong positive correlation between the two variables.
- **Bảng 5**: This table shows the correlation between economic conditions (EO), financial stability (EC), and various financial metrics (ER, ET, PVDS, ST, PVDSxET, PVDSxER, CPxET, CPxER) using the HTMT system. The correlation coefficients range from 0.054 to 0.236, indicating a moderate to strong correlation between the variables.

### Conclusion:
The paper provides valuable insights into the relationship between economic conditions and financial stability, using the HTMT system. The correlation coefficients in both tables suggest that there is a significant relationship between these variables, which can be useful for investors and policymakers in making informed decisions.
- Text Content: [IMAGE ANALYSIS]
The image is a page from a research paper, specifically from the journal "Kieu Anh Tai va cong su." The paper is titled "Kieu Anh Tai va cong su. HCMCOUJS-Kinh te va Quan tri Kinh doanh, 20(10), 54-70." The page number is 63.

The content of the page is divided into two main sections, each containing a table of data. The first section is titled "Bảng 4" and the second section is titled "Bảng 5."

### Table 4:
- **Title:** Kết quả Đồ tin Cây và Giá trị Hồi Tự (Mô Hình Nghĩa Cư)
- **Columns:**
  - **Khái niệm:** This column lists the variables or concepts being measured.
  - **Hệ số tài ngài:** This column represents the correlation coefficients.
  - **Cronbach Alpha:** This column represents the Cronbach's alpha coefficients.
  - **CR:** This column represents the Cronbach's alpha coefficients.
  - **AVE:** This column represents the average variance extracted.

### Table 5:
- **Title:** Kết quả Giá trị Phân Biệt (Mô Hình Nghĩa Cư) theo Hệ Số HTMT
- **Columns:**
  - **CP:** This column represents the correlation coefficients.
  - **DG:** This column represents the correlation coefficients.
  - **EC:** This column represents the correlation coefficients.
  - **EO:** This column represents the correlation coefficients.
  - **ER:** This column represents the correlation coefficients.
  - **ET:** This column represents the correlation coefficients.
  - **PVDS:** This column represents the correlation coefficients.
  - **ST:** This column represents the correlation coefficients.
  - **PVDSxET:** This column represents the correlation coefficients.
  - **PVDSxER:** This column represents the correlation coefficients.
  - **CPxET:** This column represents the correlation coefficients.
  - **CPxER:** This column represents the correlation coefficients.

### Analysis:
- **Table 4:** The table includes several variables such as "Định hướng doanh chư (EO)," "Năng lực doanh chư (EC)," "Đối môi khám phá (ER)," "Đối môi khai thác (ET)," "Áp lực cạnh tranh (CP)," "Nhân thức giá trị dịch vụ số hóa (PVDS)," "Số hóa (DG)," and "Dịch vụ hóa (ST)." Each variable has a corresponding correlation coefficient, Cronbach's alpha, and average variance extracted (AVE).
- **Table 5:** The table includes variables such as "DG," "EC," "EO," "ER," "ET," "PVDS," "ST," "PVDSxET," "PVDSxER," "CPxET," and "CPxER." Each variable has a corresponding correlation coefficient, Cronbach's alpha, and average variance extracted (AVE).

### Conclusion:
The tables provide a detailed analysis of the relationships between the variables, with the Cronbach's alpha coefficients indicating the internal consistency of the measures. The AVE values suggest that the variables are measuring distinct constructs, with the AVE values ranging from 0.658 to 0.892, indicating that the constructs are well-defined and distinct.

The tables are structured in a way that allows for easy comparison and interpretation of the data, making it a useful resource for researchers and practitioners in the field of business and economics.


Page 3 Visual Data:
- Description: [IMAGE ANALYSIS]
This image is a page from a document titled "HCMCOUJS-Kinh tế và Quản trị Kinh doanh, 19(6), 3-17." The page is divided into two main sections: a table and a paragraph of text.

### Table Section:
The table is titled "Công nghệ IoT áp dụng" and lists three categories of companies: Amazon Go, Octobox, and Walmart. Each category has a list of companies within that category. The table includes the following columns:
- **Nhóm của hàng**: This column lists the categories of companies.
- **Cửa hàng**: This column lists the specific companies within each category.
- **Công nghệ IoT áp dụng**: This column lists the specific technologies or applications used by each company.

Here is the table in markdown format:

```markdown
| Nhóm của hàng | Cửa hàng | Công nghệ IoT áp dụng |
|-------------|---------|---------------------|
| Nhóm 1      | Amazon Go | RFID (Nhân dạng qua bàn so với tuyền), thanh toán ảo (vitrual payment), giỏ hàng ảo (virtual carts), cảm biến (sensor technology), camera thông minh (smart camera) |
| Nhóm 2      | Octobox | Thanh toán ảo, nhận diện khuôn mặt (facial recognition), RFID, camera thông minh (smart camera) |
| Nhóm 3      | Amazon Fresh | Thanh toán tự động, RFID, xe đẩy thông minh (smart cart) |
| Nhóm 4      | Kroger | Giảm sát nhiệt độ (IoT temperature monitoring), xe đẩy thông minh, hệ thống thông minh, thanh toán tự động, RFID |
| Nhóm 5      | Sobeys | Xe đẩy thông minh, thanh toán tự động, RFID |
| Nhóm 6      | Walmart | RFID, giảm sát nhiệt độ, nhận diện từ trên kệ trung báy (digital shelf-labels) |
```

### Paragraph Section:
The paragraph discusses the impact of IoT on the supply chain and logistics of retail companies. It mentions that IoT has transformed the way companies manage their supply chains and logistics, leading to increased efficiency and reduced costs. The paragraph also highlights the role of IoT in improving customer experience and satisfaction. It concludes by stating that IoT is a key factor in the future of retail and supply chain management.

### Analysis:
The table provides a clear and concise overview of how different companies are using IoT technologies. The companies listed are Amazon Go, Octobox, Amazon Fresh, Kroger, Sobeys, and Walmart. Each company has a unique approach to integrating IoT into their operations, highlighting the versatility of IoT in various industries.

The paragraph provides a deeper understanding of the impact of IoT on retail and supply chain management. It emphasizes the importance of IoT in improving efficiency, reducing costs, and enhancing customer experience. The paragraph also highlights the role of IoT in the future of retail and supply chain management, suggesting that it will continue to play a significant role in the industry.

Overall, this page provides a comprehensive overview of how IoT is being used in the retail and supply chain sectors, highlighting the benefits and challenges of integrating IoT into these industries.
- Text Content: [IMAGE ANALYSIS]
The image is a page from a document, specifically from a Vietnamese academic journal. The page number is 5, and the title of the document is "Học Thí Minh Nguyễn và công cụ HCMCOUJS-Kinh tế và Quản trị Kinh doanh, 19(6), 3-17." The document appears to be discussing the integration of IoT (Internet of Things) technology in various sectors, particularly in the context of supply chain management and logistics.

The content is structured into several sections, each detailing different types of goods and their integration with IoT technology. The table below the text provides a detailed breakdown of how IoT is applied in various sectors:

| Nhóm của hàng | Cửa hàng | Công nghệ IoT áp dụng |
| --- | --- | --- |
| Nhóm 1 | Amazon Go | RFID (Nhân dạng qua bàn so với tuyền), thanh toán ảo (vitrual payment), giỏ hàng ảo (virtual carts), cảm biến (sensor technology), camera thông minh (smart camera) |
| Nhóm 2 | Octobox | Thanh toán ảo, nhận diện khuôn mặt (facial recognition), RFID, camera thông minh (smart camera) |
| Nhóm 3 | Amazon Fresh | Thanh toán tự động, RFID, xe đẩy thông minh (smart cart) |
| Nhóm 4 | Kroger | Giảm sát nhiệt độ (IoT temperature monitoring), xe đẩy thông minh, hệ thống thông minh, thanh toán tự động, RFID |
| Nhóm 5 | Sobeys | Xe đẩy thông minh, thanh toán tự động, RFID |
| Nhóm 6 | Walmart | RFID, giảm sát nhiệt độ, nhận diện từ trên kệ trung báy (digital shelf-labels) |

The table lists various types of goods and the specific technologies used in each category. The text explains that IoT is being integrated into various sectors to improve efficiency and reduce costs. The integration of IoT technology in supply chain management is discussed, highlighting how it can enhance the efficiency of logistics and supply chain operations.

The document also references the work of Carbone (1998) and Pantano (2014) in the context of supply chain management, and Reddy (2015) in the context of technology acceptance models (TAM). The text also mentions the impact of IoT on the supply chain, particularly in terms of reducing costs and improving efficiency.

Overall, the document provides a comprehensive overview of how IoT technology is being applied in various sectors, with a focus on supply chain management and logistics.


Page 4 Visual Data:
- Description: [IMAGE ANALYSIS]
This image is a page from a research paper titled "HCMCOUJS-Kinh tế và Quản trị Kinh doanh, 19(6), 3-17." The page number is 6. The content of the page is in Vietnamese and discusses sentiment analysis and ensemble learning in the context of machine learning. The text is written in a clear and concise style, with paragraphs and bullet points providing detailed information. The page appears to be part of a larger document, possibly a research paper or academic article.
- Text Content: [IMAGE ANALYSIS]
The image is a page from a document, specifically from a research paper or academic article. The page number is 6, and the title of the document is "HCMCOUJS-Kinh tế và Quản trị Kinh doanh, 19(6), 3-17." The text is in Vietnamese and appears to be discussing a topic related to sentiment analysis and machine learning in the context of economic and business management. The content is structured into several paragraphs, each discussing different aspects of sentiment analysis and machine learning techniques. The text is well-organized, with clear headings and subheadings to guide the reader through the different sections of the paper. The formatting includes bullet points and numbered lists, which are common in academic writing to organize information clearly. The text is in a standard font, and the layout is clean and easy to read.


Page 5 Visual Data:
- Description: [IMAGE ANALYSIS]
This image is a page from a research paper titled "HCMCOUJS-Kinh tế và Quản trị Kinh doanh, 19(6), 3-17." The page is discussing the integration of machine learning and IoT in the context of supply chain management. The content is divided into several sections, including:

1. **Introduction to the paper**:
   - The paper introduces the concept of machine learning and its application in supply chain management.
   - It highlights the importance of IoT in enhancing the efficiency and accuracy of supply chain operations.

2. **Mô hình và phương pháp nghiên cứu**:
   - The paper discusses the development and implementation of a machine learning model for supply chain management.
   - It explains how the model is designed to analyze data from various sources, such as social media, customer reviews, and product information, to predict demand and optimize inventory levels.

3. **Methodology**:
   - The methodology involves the use of machine learning algorithms, such as decision trees, random forests, and logistic regression, to analyze data from IoT devices.
   - The paper also discusses the use of Python programming language for implementing these algorithms.

4. **Results and discussion**:
   - The results of the research are presented, showing the effectiveness of the machine learning model in predicting demand and improving inventory management.
   - The paper discusses the potential applications of the model in real-world scenarios, such as optimizing supply chain operations and reducing costs.

5. **Conclusion**:
   - The paper concludes by highlighting the importance of integrating machine learning and IoT in supply chain management to improve efficiency and reduce costs.
   - It emphasizes the need for further research and development in this area to address the challenges in supply chain management.

The image also includes a flowchart that illustrates the process of data analysis and decision-making in the supply chain management process. The flowchart is divided into three main stages: data collection, data analysis, and decision-making. The stages are represented by boxes with arrows indicating the flow of data and information. The flowchart is designed to show how the data is processed and analyzed to make informed decisions about inventory levels and supply chain operations.
- Text Content: [IMAGE ANALYSIS]
The image is a page from a document, specifically from a research paper or academic article. The page number is 7, and the title of the document is "Hô Thị Minh Nguyễn và công cụ HCMCOUJS-Kinh tế và Quản trị Kinh doanh, 19(6), 3-17." The content is in Vietnamese and discusses the use of machine learning and soft voting ensemble techniques in the context of IoT (Internet of Things) and decision-making processes in the business domain.

### Page Layout:
- **Header**: The top of the page contains the title of the document and the page number.
- **Main Content**: The main body of the text is divided into several sections, each with a heading and a paragraph of text.
- **Illustrations**: There are several diagrams and flowcharts in the text, which are used to explain the concepts and processes discussed.
- **Footnotes**: There are footnotes at the bottom of the page, which provide additional information or references.

### Text Content:
1. **Introduction to the Topic**:
   - The introduction explains the importance of machine learning and soft voting ensemble techniques in the context of IoT and decision-making processes in the business domain.
   - It mentions that these techniques are used to improve the accuracy of predictions and decision-making processes in various industries.

2. **Mô hình và phương pháp nghiên cứu**:
   - This section discusses the theoretical framework and methodology used in the research.
   - It explains how the research aims to develop a soft voting ensemble model for predicting customer behavior in the context of IoT.

3. **Mô hình nghiên cứu tổng quan**:
   - This section provides a detailed overview of the research methodology and the overall research design.
   - It includes a flowchart that outlines the steps involved in the research process, including data collection, model development, and evaluation.

4. **Chuẩn bị dữ liệu**:
   - This section discusses the preparation of data for the research.
   - It explains how the data is collected and prepared for analysis, including data cleaning and preprocessing.

5. **Thử thách dữ liệu**:
   - This section discusses the challenges and limitations of the research data.
   - It highlights the need for robust data handling and analysis techniques to ensure accurate results.

6. **Conclusion**:
   - The conclusion summarizes the findings and implications of the research.
   - It highlights the potential applications of the developed model in real-world business scenarios.

### Diagrams and Flowcharts:
- The text includes several diagrams and flowcharts that illustrate the research methodology and the steps involved in the development of the soft voting ensemble model.
- These diagrams help to visualize the process of data collection, model development, and evaluation, making the information more accessible and easier to understand.

### Analysis:
The document is a detailed research paper that discusses the use of machine learning and soft voting ensemble techniques in the context of IoT and decision-making processes in the business domain. The text is well-organized, with clear headings and subheadings, making it easy to follow the research methodology and findings. The use of diagrams and flowcharts enhances the clarity and understanding of the research process, making it a valuable resource for researchers and practitioners in the field of IoT and business analytics.


Page 6 Visual Data:
- Description: [IMAGE ANALYSIS]
This image appears to be a page from a document, specifically a research paper or academic article. The page number is 8, and the title at the top of the page is "Họ Thị Minh Nguyễn và công cụ HCMCOUJS-Kinh tế và Quản trị Kinh doanh, 19(6), 3-17." The content of the page is divided into several sections, including a table and a flowchart.

### Table Section:
The table is titled "Hình 2. Các bước tiên xử lý dữ liệu" which translates to "Image 2. Steps in data preprocessing." The table has three columns: "Quy trình" (Process), "Trước" (Before), and "Sau" (After). The rows are labeled with specific steps in the preprocessing process. The steps are as follows:

1. **Xóa URL**
2. **Xóa tag HTML**
3. **Chuyển từ chữ thường + Chuyển hóa từ Việt tắt (chatwords + contractions)**
4. **Chuyển emoticon + emoji và động chữ**
5. **Đưa từ vựng nguyên mẫu (Lemmatize)**
6. **Xóa giây từ ngoại lai**
7. **Xóa giây từ ròng**
8. **Xóa từ dùng (stopwords)**
9. **Xóa từ dùng (stopwords)**
10. **Xóa từ dùng (stopwords)**

### Flowchart Section:
The flowchart is titled "Hình 2. Các bước tiên xử lý dữ liệu" and is labeled with the same steps as the table. The flowchart shows the sequence of steps in the data preprocessing process, with arrows indicating the flow from one step to the next.

### Markdown Format:
```markdown
# Hình 2. Các bước tiên xử lý dữ liệu

## Quy trình
1. Xóa URL
2. Xóa tag HTML
3. Chuyển từ chữ thường + Chuyển hóa từ Việt tắt (chatwords + contractions)
4. Chuyển emoticon + emoji và động chữ
5. Đưa từ vựng nguyên mẫu (Lemmatize)
6. Xóa giây từ ngoại lai
7. Xóa giây từ ròng
8. Xóa từ dùng (stopwords)
9. Xóa từ dùng (stopwords)
10. Xóa từ dùng (stopwords)

## Hành trình
1. Xóa URL
2. Xóa tag HTML
3. Chuyển từ chữ thường + Chuyển hóa từ Việt tắt (chatwords + contractions)
4. Chuyển emoticon + emoji và động chữ
5. Đưa từ vựng nguyên mẫu (Lemmatize)
6. Xóa giây từ ngoại lai
7. Xóa giây từ ròng
8. Xóa từ dùng (stopwords)
9. Xóa từ dùng (stopwords)
10. Xóa từ dùng (stopwords)
```

### Analysis:
The table and flowchart provide a clear and structured overview of the steps involved in data preprocessing. The table lists the steps in detail, while the flowchart shows the sequence of these steps in a visual format. This is useful for understanding the process and identifying any potential issues or inefficiencies in the data preprocessing steps.

### Conclusion:
This page from the document provides a comprehensive overview of the data preprocessing steps, which is crucial for ensuring the accuracy and reliability of the data analysis. The table and flowchart are designed to help readers understand the process and identify any potential issues or inefficiencies in the data preprocessing steps.
- Text Content: [IMAGE ANALYSIS]
The image is a page from a document, specifically from a research paper or academic article. The page number is 8, and the title of the document is "Hô Thị Minh Nguyễn và công cụ HCMCOUJS-Kinh tế và Quản trị Kinh doanh, 19(6), 3-17." The content is divided into several sections, each containing text and diagrams.

### Section 1: Introduction
- The introduction discusses the use of various tools and techniques in the field of economics and management, specifically mentioning the use of HCMCOUJS-Kinh tế and management tools.

### Section 2: Tools and Techniques
- This section lists several tools and techniques used in the field of economics and management, including Selenium, Octoparse, PhantomBuster, TikTok API, and others.
- It also mentions the use of various APIs and tools for data analysis and management.

### Section 3: Case Studies
- The section includes two case studies:
  - **Case Study 1**: Amazon Go
  - **Case Study 2**: Walmart
- Each case study includes a brief description of the store and the products sold.

### Section 4: Process Flow Diagrams
- The section includes a flow diagram for the process of data analysis and management, which includes steps such as:
  - **1. Xóa URL**: Remove the URL from the text.
  - **2. Xóa tag HTML**: Remove HTML tags.
  - **3. Chuyển từ chữ thường + Chuyển hóa từ Việt tắt (chatwords + contractions)**: Convert words to standard form and vice versa.
  - **4. Chuyển emoticon + emoji và động chữ**: Convert emoticons and emojis.
  - **5. Đưa từ vựng nguyên mẫu (Lemmatize)**: Lemmatize the words.
  - **6. Tách câu sau but/and/except/đầu chấm**: Separate the sentence after but, and, except, and the start of the sentence.
  - **7. Xóa số, dấu câu, ký tự là**: Remove numbers, punctuation, and special characters.
  - **8. Xóa từ đúng (stopwords)**: Remove stopwords.
  - **9. Xóa giây từ ngoại lai**: Remove foreign words.
- The flow diagram is labeled with the steps in blue boxes.

### Section 5: Conclusion
- The conclusion summarizes the findings and the importance of the tools and techniques discussed in the paper.

### Section 6: References
- The references section lists the sources used in the paper.

### Analysis
The document appears to be a research paper or academic article discussing the use of various tools and techniques in the field of economics and management. The introduction provides an overview of the topic, while the case studies and flow diagrams provide practical examples of how these tools can be used in real-world scenarios. The conclusion summarizes the findings and highlights the importance of the discussed tools and techniques.


Page 7 Visual Data:
- Description: [IMAGE ANALYSIS]
This image is a page from a research paper, specifically from the journal "HCMCOUJS-Kinh tế và Quản trị Kinh doanh" (Vietnamese Journal of Economics and Management). The page number is 9. The paper appears to be discussing statistical analysis and data visualization techniques, specifically focusing on "Phân tích dữ liệu khám phá (EDA)" (Exploratory Data Analysis).

The main focus of the page is on two box plots labeled "Hình 3" and "Hình 4," which represent the distribution of word counts in two different contexts. The left box plot in "Hình 3" shows a distribution with a higher concentration of data points around the mean, indicating a more central tendency. The right box plot in "Hình 4" shows a more spread-out distribution, with a higher number of outliers, indicating a more dispersed data set.

Below the box plots, there is a table that provides statistical summaries of the data. The table includes the following columns: count, mean, std, min, 25%, 50%, 75%, and max. The count column shows the total number of data points, the mean is the average word count, std is the standard deviation, min is the minimum word count, 25% and 50% are the lower and upper quartiles, 75% is the upper quartile, and max is the maximum word count.

The table provides insights into the distribution of word counts across different contexts, which could be useful for understanding the variability and central tendency of the data. The box plots and the table together provide a comprehensive view of the data's distribution and central tendency, which is crucial for further analysis and interpretation.

Overall, this page is a valuable resource for anyone interested in statistical analysis and data visualization, particularly in the context of Exploratory Data Analysis.
- Text Content: [IMAGE ANALYSIS]
The image is a page from a document, specifically from a research paper or academic article. The page number is 9, and the title of the page is "3.2.3. Phân tích dữ liệu khám phá (EDA)" which translates to "Exploratory Data Analysis (EDA)" in English. The page contains text in Vietnamese and includes two figures and a table.

### Figures:
1. **Figure 3:**
   - Title: Xác định các ngoái lại
   - Description: This figure shows a box plot of word count distribution. The x-axis represents the word count, and the y-axis represents the number of occurrences. The box plot includes the median, quartiles, and outliers.

2. **Figure 4:**
   - Title: Sau khi xử lý các ngoái lại
   - Description: This figure shows a box plot of word count distribution after applying a data cleaning process. The x-axis represents the word count, and the y-axis represents the number of occurrences. The box plot includes the median, quartiles, and outliers.

### Table:
The table is titled "Thông tin bộ dữ liệu trên phân tích từ phân vị" which translates to "Information on data on the analysis from the position." The table contains the following columns:
- **Số ký tự:** Number of characters
- **Số lượng từ:** Number of words
- **Độ dài từ trung bình:** Average word length

### Analysis:
The table provides statistical information about the word count distribution in the dataset. The average word length is 6.24 characters, with a standard deviation of 4.98 characters. The minimum word length is 1.00 characters, and the maximum word length is 718.00 characters. The table also includes the 25%, 50%, and 75% quantiles, which are 3.00, 5.00, and 8.00 characters, respectively. The maximum word length is 704.00 characters, which is the highest value in the dataset.

### Conclusion:
The document appears to be discussing exploratory data analysis techniques, specifically focusing on word count distribution and data cleaning. The figures and table provide insights into the characteristics of the data, such as the distribution of word lengths and the presence of outliers. This information is crucial for understanding the nature of the data and making informed decisions about further analysis or data processing.


Page 8 Visual Data:
- Description: [IMAGE ANALYSIS]
This image appears to be a page from a research paper or academic article. The page number is 10, and the title of the page is "3.3. Gán nhân quan điểm cho bình luận qua phương pháp phân loại 03 lớp." The content of the page discusses a method for classifying comments into three classes using a sentiment reasoning approach.

The page contains a table with four columns and five rows, detailing data for different comments. The columns are labeled as follows:
- "Tên tài khoản" (Username)
- "Thời gian" (Time)
- "Câu hỏi" (Question)
- "Bình luận" (Comment)
- "Chi số" (Score)

The table includes the following data points for each comment:
- "Jenae K." on 01-06-2018 with Amazon Go
- "Rahul Soni" on 03-09-2020 with Walmart
- "Jenae K." on 01-06-2018 with Amazon Go
- "product shelf sensor know grab item"

The table also includes the sentiment scores for each comment, ranging from -1 to 1, with positive scores indicating positive sentiment, negative scores indicating negative sentiment, and neutral scores indicating neutral sentiment.

The table is labeled as "Bảng 5" (Table 5) and is part of a larger section titled "Kết quả gán nhân quan điểm trên phương pháp VADER."

The page also includes a section titled "4. Kết quả thực nghiệm và đánh giá" (4. Results and Evaluation), which discusses the results and evaluation of the sentiment analysis method.

Overall, the page provides a detailed analysis of how sentiment analysis can be used to classify comments into different categories, using a specific method called VADER (Valence Aware Dictionary and Sentiment Reasoner).
- Text Content: [IMAGE ANALYSIS]
The image is a page from a document, specifically from a section titled "3.3. Gán nhân quan điểm cho bình luận qua phương pháp phân loại 03 lớp." The page number is 10, and the document is titled "Hồ Thị Minh Nguyễn và công cụ HCMCOUJS-Kinh tế và Quản trị Kinh doanh, 19(6), 3-17." The content is in Vietnamese and discusses a method for classifying comments into three classes using a sentiment analysis tool called VADER (Valence Aware Dictionary and Sentiment Reasoner).

The page contains a table with five columns and five rows, detailing different comments and their sentiment scores. The table is structured as follows:

| Tên tài khoản | Thời gian | Câu hỏi | Bình luận | Chi số | Điểm quan điểm | Quan điểm |
|-------------|---------|-------|----------|------|-------------|---------|
| Jenae K.   | 01-06-2018 | Amazon Go | store awesome super cool concept definitely see... | {'neg': 0.0, 'neu': 0.487, 'pos': 0.51} | 0.9136       | positive |
| Rahul Soni | 03-09-2020 | Walmart | bad system customer service | {'neg': 0.399, 'neu': 0.28, 'pos': 0.322} | -0.2732      | negative |
| Jenae K.   | 01-06-2018 | Amazon Go | product shelf sensor know grab item | {'neg': 0.0, 'neu': 1.0, 'pos': 0.0} | 0.0000      | neutral |

The table also includes a note at the bottom indicating the source of the data: "Nguồn: Nhóm tác giả."

The document appears to be discussing a method for sentiment analysis using the VADER tool, which is used to analyze the sentiment of text. The table shows examples of comments and their corresponding sentiment scores, which are then used to classify the comments into three categories: positive, negative, and neutral.

The layout of the page is straightforward, with clear headings and subheadings for each section, making it easy to navigate and understand the content. The table provides a structured way to present the data, allowing for easy comparison and analysis of the sentiment scores for each comment.


Page 9 Visual Data:
- Description: [IMAGE ANALYSIS]
This image is a page from a book or academic paper, specifically from a section titled "Bảng 6" (Table 6). The table is titled "Tham số mô hình máy học dùng trong phân tích quan điểm bình luận" (Model parameters used in sentiment analysis), and it lists various machine learning models and their corresponding parameters. The table includes the following columns:

- **Tham số mô hình**: This column lists the parameters of each model.
- **KNN**: n_neighbors: 1
- **Decision tree**: criterion: gini, min_samples_leaf: 2, min_samples_split: 9, min_weight_fraction_leaf: 0
- **Hội quy logistic**: C: 10, max_iter: 100, penalty: l1, solver: saga
- **Random forest**: n_estimators: 100, criterion: gini, max_depth: None, min_samples_split: 2, min_samples_leaf: 1, min_weight_fraction_leaf: 0, max_features: sqrt
- **Mô hình kết hợp**: Các thuật toán tham gia vào mô hình học kết hợp được tổ chức bởi các tham số mô hình như trên

The text below the table provides a brief explanation of the models and their parameters, along with a diagram illustrating the process of combining models for sentiment analysis. The diagram shows how the models are connected and how they contribute to the final model.

The text also mentions the following points:
- **4.2. Mô hình học kết hợp cho phân tích quan điểm**: This section discusses the combination of models for sentiment analysis.
- **4.3. Dánh giá mô hình**: This section evaluates the models based on various metrics such as Accuracy, F1-score, Recall, and Precision.
- **4.3. Kết quả thực nghiệm**: This section presents the experimental results, showing that the model achieves an accuracy of 0.89.

Overall, the image provides a comprehensive overview of the models and their parameters used in sentiment analysis, along with a detailed explanation of the process and evaluation of the models.
- Text Content: [IMAGE ANALYSIS]
The image is a page from a document, specifically from a Vietnamese academic journal. The page number is 11, and the title of the page is "Bảng 6" which translates to "Table 6." The document appears to be discussing machine learning algorithms and their applications in a specific context, likely related to decision-making processes.

### Table Description:
The table is titled "Tham so mô hình máy học dùng trong phân tích quan điểm bình luận" which translates to "Tham so of machine learning models used in the analysis of opinion comments." The table lists various machine learning models and their parameters:

1. **KNN (K-Nearest Neighbors)**:
   - n_neighbors: 1

2. **Decision tree**:
   - criterion: gini, min_samples_leaf: 2, min_samples_split: 9, min_weight_fraction_leaf: 0

3. **Hội quy logistic**:
   - C: 10, max_iter: 100, penalty: l1, solver: saga

4. **Random forest**:
   - n_estimators: 100, criterion: gini, max_depth: None, min_samples_split: 2, min_samples_leaf: 1, min_weight_fraction_leaf: 0, max_features: sqrt

5. **Mô học kết hợp**:
   - Các thuật toán tham gia vào mô hình học kết hợp được tổ chức bởi các tham số mô hình như trên

### Diagram Description:
The diagram below the table shows the flow of data through the machine learning models:

1. **Data Input**:
   - A dataset is input into the system.

2. **Processing**:
   - The data is processed through the machine learning models.

3. **Output**:
   - The output is the model predictions or classifications.

### Analysis:
The table and diagram together provide a clear overview of the machine learning models and their respective parameters. The models listed are commonly used in text analysis and opinion mining, which involves analyzing and interpreting text data to extract meaningful insights.

### Relevant Knowledge:
Machine learning models such as KNN, Decision Trees, Random Forest, and Hoi Quy Logistic are used in various fields, including natural language processing, sentiment analysis, and opinion mining. These models are used to classify or predict the sentiment of text data based on the input data.

### Conclusion:
The page provides a detailed overview of machine learning models and their parameters, which can be useful for researchers and practitioners in the field of machine learning and text analysis. The diagram helps to visualize the flow of data through the models, making it easier to understand how the models work together to make predictions or classifications.


Page 10 Visual Data:
- Description: [IMAGE ANALYSIS]
This image is a page from a research paper, specifically from the journal "HCMCOUJS-Kinh tế và Quản trị Kinh doanh, 19(6), 3-17." The page is titled "Bảng 7: Kết quả kiểm định chéo của mô hình học dự đoán quan điểm trên tập huấn luyện."

The table on the page compares the performance metrics of various machine learning models on a dataset. The models listed are KNN, Decision tree, Random forest, Hoi quy logistic, and a hybrid logistic model. The metrics compared include Mean Precision, Mean Recall, Mean F1 Score, Mean Accuracy, and Mean ROC AUC Score.

The table shows that the hybrid logistic model has the highest Mean F1 Score (0.88) and Mean ROC AUC Score (0.97), indicating it performs the best in terms of both precision and recall. The KNN model has the lowest Mean F1 Score (0.42) and Mean ROC AUC Score (0.62), suggesting it performs the worst.

Below the table, there is a ROC (Receiver Operating Characteristic) curve graph. The graph shows the trade-off between True Positive Rate (TPR) and False Positive Rate (FPR) for different models. The ROC curve for the hybrid logistic model is the highest, indicating it has the best balance between true positive and false positive rates.

The text on the page explains that the ROC curve is used to evaluate the performance of a binary classification model. The area under the ROC curve (AUC) is a measure of the model's ability to distinguish between classes. A higher AUC value indicates better performance.

The text also mentions that the AUC score for the hybrid logistic model is 0.97, which is the highest among the listed models. The text further explains that the AUC score is a measure of the model's ability to distinguish between classes, and a score of 1 indicates perfect discrimination.

Overall, the image provides a clear comparison of the performance metrics and ROC curve for different machine learning models, highlighting the hybrid logistic model's superior performance.
- Text Content: [IMAGE ANALYSIS]
The image is a page from a document, specifically from a research paper. The page number is 12, and the title of the page is "Bảng 7 Kết quả kiểm định chéo của mô hình học dự đoán quan điểm trên tập huấn luyện." This translates to "Table 7: ROC Curve Results of the Model for Predicting the Opinion on Training Dataset."

The table on the page contains the following columns and rows:

| Phương pháp máy học | Mean Precision | Mean Recall | Mean F1 Score | Mean Accuracy | Mean ROC AUC Score |
|-------------------|----------------|------------|----------------|--------------|-----------------|
| KNN               | 0.68           | 0.47       | 0.42           | 0.49         | 0.62             |
| Decision tree    | 0.85           | 0.86       | 0.85           | 0.86         | 0.89             |
| Random forest    | 0.88           | 0.87       | 0.88           | 0.88         | 0.96             |
| Hồi quy logistic  | 0.87           | 0.87       | 0.87           | 0.88         | 0.96             |
| Mô hình kết hợp    | 0.89           | 0.88       | 0.88           | 0.89         | 0.97             |

The table shows the performance metrics for various machine learning models on a training dataset. The metrics include Mean Precision, Mean Recall, Mean F1 Score, Mean Accuracy, and Mean ROC AUC Score.

Below the table, there is a graph titled "Hình 6. Đường cong ROC các mô hình dự đoán quan điểm trên tập huấn luyện" which translates to "Graph 6: ROC Curve of the Models for Predicting the Opinion on Training Dataset."

The graph shows the ROC curve for different models, with the x-axis representing the False Positive Rate and the y-axis representing the True Positive Rate. The models included in the graph are Logistic Regression, Decision Tree, KNN, Random Forest, and Ensemble.

The text below the graph explains the ROC curve and its significance in evaluating the performance of machine learning models. It mentions that the ROC curve is a plot of the true positive rate against the false positive rate at various threshold settings, and it is used to evaluate the trade-off between false positives and false negatives.

The text also discusses the importance of the Area Under the ROC Curve (AUC) score, which is a measure of the model's ability to distinguish between classes. A higher AUC score indicates better performance.

The text concludes with a section titled "4.4. Trực quan hóa và phân tích kết quả," which translates to "4.4. Quantitative and Analytical Results," and it discusses the results of the model's performance on the training dataset.

Overall, the page provides a detailed analysis of the performance of different machine learning models on a training dataset, using various metrics and graphical representations to illustrate the model's ability to predict opinions.


Page 1 Visual Data:
- Description: [IMAGE ANALYSIS]
This image is a promotional graphic for a report titled "Understanding Vietnam Retail Market." The background is a deep blue, and the text is prominently displayed in white and blue fonts. The title is centered at the top, and the subtitle is placed below it. The logo of Nielsen Consumer LLC is visible at the bottom left corner, indicating the source of the report.

On the right side of the image, there is a circular inset that features a photograph of a street scene in Vietnam. The scene shows several people on motorbikes, each carrying baskets filled with various fruits and vegetables. The baskets are filled with a variety of items, including bananas, coconuts, and other produce. The people are engaged in their activities, likely selling or transporting the produce.

The overall design of the image is clean and professional, with a focus on the report's title and the visual representation of the Vietnamese retail market. The Nielsen logo suggests that the report is a comprehensive analysis of the retail market in Vietnam, providing insights and data for businesses and investors interested in the Vietnamese retail sector.
- Text Content: [IMAGE ANALYSIS]
The image is a promotional slide for understanding the Vietnam retail market. The slide has a dark blue background with a circular blue border on the right side. The main text is in white and blue, with the title "Understanding Vietnam Retail Market" in the center. Below the title, the logo "NIQ" is displayed in white.

On the left side of the slide, there is a circular image showing a street scene with several people on motorbikes, surrounded by various baskets filled with fruits and vegetables. The image is taken from an aerial perspective, providing a top-down view of the market. The text "© 2023 Nielsen Consumer LLC. All Rights Reserved." is displayed at the bottom of the slide in white text.


Page 2 Visual Data:
- Description: [IMAGE ANALYSIS]
This image is a promotional graphic for a Vietnam economy update by Nielsen Consumer LLC. The background is a deep blue with a circular blue border. The main title, "Vietnam Economy Update," is prominently displayed in white text with a blue outline. Below the main title, the logo of Nielsen Consumer LLC is shown in blue text.

In the circular inset, there is a photograph of three women sitting at a conference table. They appear to be engaged in a discussion, with one woman holding a laptop and another holding a pen. The setting looks like a modern office environment, with laptops, papers, and a plant on the table. The overall design of the image is professional and focused on providing information about the Vietnam economy.
- Text Content: [IMAGE ANALYSIS]
The image is a promotional graphic for a Vietnam economy update by Nielsen Consumer LLC. The layout is divided into two main sections: the left side features a dark blue background with white and blue text, and the right side shows a photograph of three people in a meeting room.

### Left Side:
- **Text**:
  - "Vietnam"
  - "Economy Update"
  - "NIQ"
- **Logo**:
  - The logo "NIQ" is displayed in blue and white.

### Right Side:
- **Photograph**:
  - A photograph shows three people sitting at a conference table. They appear to be engaged in a discussion or meeting.
  - The table is set with laptops, papers, and a plant.
  - The background includes a whiteboard with graphs and charts.
- **Text**:
  - "Vietnam Economy Update"
  - "NIQ" is repeated in the same blue and white color scheme as the logo.

### Additional Information:
- **Copyright**:
  - "© 2023 Nielsen Consumer LLC. All Rights Reserved."

### Analysis:
The image is designed to attract attention to the Vietnam economy update by highlighting the involvement of three people in a meeting setting. The use of a professional photograph and the presence of graphs and charts on the whiteboard suggests that the update is likely to be informative and possibly related to economic trends or developments in Vietnam. The logo "NIQ" suggests that the source of the update is a reputable company, likely providing insights or data on the Vietnamese economy.

### Conclusion:
The layout effectively uses contrasting colors and imagery to draw attention to the content of the Vietnam economy update. The professional setting and the inclusion of graphs and charts indicate that the update is likely to be informative and possibly related to economic data or trends in Vietnam.


Page 3 Visual Data:
- Description: [IMAGE ANALYSIS]
This image is an infographic that provides a comprehensive overview of Vietnam's economy and its growth compared to APAC and South East Asia. The infographic is divided into two main sections: a line graph and a pie chart.

### Line Graph
The line graph on the left side of the image shows the real GDP growth of Vietnam, APAC, and South East Asia from 2020 to 2025. The graph is color-coded to differentiate between the three regions:
- **Vietnam**: Green
- **APAC**: Blue
- **South East Asia**: Brown

The line graphs for Vietnam and APAC show a similar trend, with both experiencing a decline in GDP growth in 2020 and 2021. However, Vietnam's GDP growth starts to recover in 2022 and continues to grow steadily, while APAC's GDP growth remains relatively flat. South East Asia's GDP growth shows a slight increase in 2022 but then decreases again.

### Pie Chart
The pie chart on the right side of the image provides a detailed breakdown of the GDP growth by sectors for Vietnam and APAC for the years 2023 and 2024. The sectors are:
- **Agriculture, Forestry, and Fishery**: Green
- **Industrial and Construction**: Blue
- **Services**: Pink

The pie chart shows that Vietnam's GDP growth is primarily driven by services, with a significant contribution from the services sector. APAC's GDP growth is more balanced, with contributions from both services and industrial and construction sectors. South East Asia's GDP growth is relatively low, with a smaller contribution from services.

### Sustainable & Golden Population
The infographic includes data on the total population, balance gender, and the Golden Ratio for Vietnam. The total population is projected to be 101 million by 2024, making Vietnam the 3rd largest population in Southeast Asia. The balance gender ratio is 99.2 male per 100 female, which is higher than the average for Southeast Asia. The Golden Ratio, which is the ratio of males to females, is 99.2 male per 100 female, indicating a higher male population.

### Top 5 Investors in 2024
The infographic also includes data on the top 5 investors in Vietnam for the year 2024. The data shows that Singapore is the top investor, followed by South Korea, Japan, and China. The investment capital is represented by the number of investment rounds, with each round represented by a bar.

### Conclusion
The infographic provides a clear and concise overview of Vietnam's economic growth and its comparative performance with APAC and South East Asia. It highlights the country's strong growth in services and its projected future growth as the 2nd largest economy in Southeast Asia. The data on the Golden Ratio and the balance gender ratio also contribute to a better understanding of Vietnam's demographic and economic characteristics.
- Text Content: [IMAGE ANALYSIS]
The image is an infographic that provides a detailed analysis of Vietnam's economy and its growth compared to other regions in the APAC (Asia-Pacific) and South East Asia. The infographic is divided into two main sections: a graph and a pie chart.

### Graph Section:
The graph shows the real GDP growth of Vietnam, APAC, and South East Asia from 2020 to 2025. The graph is divided into three lines representing Vietnam, APAC, and South East Asia. The lines show a general upward trend for Vietnam and a downward trend for APAC and South East Asia. The graph includes the following data points:
- 2020: -3.5% for Vietnam, -0.8% for APAC, and 4.1% for South East Asia.
- 2021: 2.6% for Vietnam, 2.9% for APAC, and 5.8% for South East Asia.
- 2022: 4.3% for Vietnam, 5.1% for APAC, and 5.8% for South East Asia.
- 2023: 7.2% for Vietnam, 8.5% for APAC, and 5.1% for South East Asia.
- 2024: 7.1% for Vietnam, 4.8% for APAC, and 4.5% for South East Asia.
- 2025: 5.2% for Vietnam, 3.9% for APAC, and 3.9% for South East Asia.

### Pie Chart Section:
The pie chart is titled "Fueled by Servcies and Industrial & Construction." It shows the percentage contribution to the 2024 GDP by sectors:
- Agriculture, Forestry, and Fishery: 38%
- Industrial & Construction: 42%
- Services: 12%

### Sustainable & Golden Population Section:
The section provides data on the total population, balance gender, and Golden Ratio. The data includes:
- Total Pop: 101 million
- Balance gender: 99.2 male per 100 female
- Golden Ratio: 99.2 male per 100 female

### Top 5 Investors in 2024 Section:
The section lists the top 5 investors in 2024:
- #1: Singapore
- #2: South Korea
- #3: Japan
- #4: China
- #5: Vietnam

### Summary:
The infographic provides a comprehensive overview of Vietnam's economic growth and its contribution to the APAC and South East Asia regions. It highlights the positive trends in Vietnam's economy, particularly in the services and industrial sectors, and the demographic trends. The data is sourced from the IMF and World Economic Leauge Table 2024.


Page 4 Visual Data:
- Description: [IMAGE ANALYSIS]
This image is a promotional graphic for a report on the Vietnam retail landscape. The background is a deep blue with a circular blue border on the right side. The left side of the image features the title "Vietnam Retail Landscape" in white text, with the word "NIQ" in blue text at the bottom.

In the circular image on the right, there is a woman holding a shopping basket in a grocery store. The woman is wearing a brown dress and appears to be in the middle of a shopping trip. The background of the circular image is a blurred image of a grocery store aisle, showing various products on shelves. The overall design is clean and professional, with a focus on the retail landscape of Vietnam.
- Text Content: [IMAGE ANALYSIS]
Vietnam
Retail Landscape

NIQ


Page 6 Visual Data:
- Description: [IMAGE ANALYSIS]
This image is a slide from a presentation, likely related to market analysis or channel landscape. The slide is titled "Channel Landscape" and is numbered "1" at the top. The slide asks, "How is market structured by channels?"

The slide features a circular design with a blue and white color scheme. On the left side of the slide, there is a large white circle with a blue border. Inside this circle, the text "Channel Landscape" is written in blue, followed by the question "How is market structured by channels?" in white.

On the right side of the slide, there is a photograph of a woman shopping in a grocery store. She is holding a shopping basket and appears to be examining a product. The background of the photograph shows the interior of the store with shelves filled with various products.

At the bottom of the slide, there is a logo with the text "NIQ" and the copyright notice "© 2023 Nielsen Consumer LLC. All Rights Reserved." The slide number "6" is also visible at the bottom right corner.

Overall, the slide appears to be part of a larger presentation on market analysis, specifically focusing on the structure of the market by different channels.
- Text Content: [IMAGE ANALYSIS]
The image is a slide from a presentation, likely related to market analysis or consumer behavior. The slide is titled "1] Channel Landscape" and contains the following text:

---

**[1] Channel Landscape**
How is market structured by channels?

---

The slide is divided into two main sections:

1. **Title Section:**
   - The title is written in bold, blue text and is centered at the top of the slide.
   - Below the title, there is a question in white text: "How is market structured by channels?"

2. **Image Section:**
   - The image on the right side of the slide shows a woman shopping in a grocery store.
   - She is holding a shopping basket and appears to be examining a product.
   - The background of the image shows a well-lit grocery store with shelves filled with various products.
   - The image is framed by a circular blue border.

3. **Footer Section:**
   - At the bottom of the slide, there is a logo and text that reads: "© 2023 Nielsen Consumer LLC. All Rights Reserved."
   - The slide number "6" is displayed at the bottom right corner.

The layout is simple and straightforward, with a clear focus on the title and the image of the woman shopping. The slide appears to be part of a larger presentation, possibly discussing the distribution and structure of the market by different channels.


Page 8 Visual Data:
- Description: [IMAGE ANALYSIS]
This image is a slide from a presentation that discusses changes in retail trends and consumer behaviors over the past five years. The slide is divided into two main sections: a bar graph and a timeline diagram.

### Bar Graph
The bar graph on the left side of the slide shows the value growth of FMCG (Fast-Moving Consumer Goods) in the retail sector from FY20 to FY24. The x-axis represents the fiscal years (FY), and the y-axis represents the value growth percentage. The graph includes three bars for each year:
- **FY20**: -7.1%
- **FY21**: -7.7%
- **FY22**: -4.0%
- **FY23**: -2.4%
- **FY24**: 1.2%

### Timeline Diagram
The timeline diagram on the right side of the slide provides a visual representation of the changes in retail trends and consumer behaviors over the five years. The timeline is divided into four main sections:
1. **2021**: The year is marked as "Interrupted by pandemic."
2. **2022**: The year is marked as "Inflation."
3. **2023**: The year is marked as "Crisis in living cost."
4. **2024**: The year is marked as "Volume recovery."
5. **2025**: The year is marked as "New normal."

### Key Points:
1. **2021**: The year marked as "Interrupted by pandemic" suggests that the pandemic had a significant impact on retail trends and consumer behaviors.
2. **2022**: The year marked as "Inflation" indicates that the cost of living increased, which could have affected consumer spending and retail sales.
3. **2023**: The year marked as "Crisis in living cost" suggests that the economic situation became more challenging, leading to increased consumer uncertainty and spending.
4. **2024**: The year marked as "Volume recovery" indicates that retail sales began to recover, with a focus on volume growth.
5. **2025**: The year marked as "New normal" suggests that the retail industry is moving towards a new normal, with a focus on sustainability, digital transformation, and consumer behavior changes.

### Analysis:
The timeline diagram provides a clear overview of how retail trends and consumer behaviors have evolved over the past five years. The pandemic in 2021 disrupted the retail landscape, leading to increased inflation and a crisis in living costs. In 2022, inflation continued to impact consumer spending, while 2023 saw a shift towards a crisis in living costs, which could have led to increased consumer uncertainty and spending. In 2024, retail sales began to recover, with a focus on volume growth. Finally, in 2025, the retail industry is moving towards a new normal, with a focus on sustainability, digital transformation, and consumer behavior changes.

### Conclusion:
This slide provides a comprehensive overview of how retail trends and consumer behaviors have evolved over the past five years, highlighting the impact of the pandemic, inflation, and economic crises on the retail sector. The timeline diagram helps to visualize the changes and provides a clear understanding of the current retail landscape and future trends.
- Text Content: [IMAGE ANALYSIS]
The image is a slide from a presentation that discusses changes in retail trends and consumer behaviors over the past five years. The slide is divided into two main sections: a bar graph and a timeline diagram.

### Bar Graph
The bar graph on the left side of the slide shows the value growth of FMCG (Fast-Moving Consumer Goods) in the retail sector from FY20 to FY24. The x-axis represents the fiscal years (FY20 to FY24), and the y-axis represents the value growth percentage. The bars are color-coded to represent different price changes:
- Green: Price increase
- Gray: Price decrease
- Black: Nominal value growth

The graph shows the following values:
- FY20: -7.1%
- FY21: -7.7%
- FY22: -4.0%
- FY23: -2.4%
- FY24: 1.2%

### Timeline Diagram
The timeline diagram on the right side of the slide provides a visual representation of the changes in retail trends and consumer behaviors over the next five years. The timeline is divided into four main periods:
1. **2021**: The period is marked as "Interrupted by pandemic."
2. **2022**: The period is marked as "Inflation."
3. **2023**: The period is marked as "Crisis in living cost."
4. **2024**: The period is marked as "Volume recovery."
5. **2025**: The period is marked as "New normal."

### Key Points:
1. **2021**: The period is marked as "Interrupted by pandemic." This suggests that the pandemic had a significant impact on retail trends and consumer behaviors during this period.
2. **2022**: The period is marked as "Inflation." This indicates that inflation was a major factor affecting retail trends and consumer behaviors during this period.
3. **2023**: The period is marked as "Crisis in living cost." This suggests that the crisis in living costs had a significant impact on retail trends and consumer behaviors during this period.
4. **2024**: The period is marked as "Volume recovery." This indicates that the volume of sales and consumer behavior started to recover during this period.
5. **2025**: The period is marked as "New normal." This suggests that the retail trends and consumer behaviors are expected to return to a new normal state in the future.

### Analysis:
The timeline diagram provides a clear and concise overview of the changes in retail trends and consumer behaviors over the past five years. The data in the bar graph shows that the FMCG sector experienced significant changes during this period, with price increases and nominal value growth being the main factors. The timeline diagram highlights the impact of various factors, such as the pandemic, inflation, living cost crisis, and volume recovery, on retail trends and consumer behaviors.


Page 9 Visual Data:
- Description: [IMAGE ANALYSIS]
This image is a comprehensive analysis of the FMCG (Fast-Moving Consumer Goods) market trends, focusing on the impact of various categories on the overall market dynamics. The image is divided into two main sections: a bar chart and a stacked bar chart.

### Bar Chart:
The bar chart shows the value contribution and growth of different FMCG categories over the last 12 months. The categories are:
- PERSONAL CARE
- HOME CARE
- IMPULSE FOOD
- STAPLE FOOD
- MILK BASES
- CIGARETTE
- BEVERAGE
- BEER

The x-axis represents the categories, and the y-axis represents the value contribution and growth in percentage terms. The bars are color-coded to differentiate between the categories:
- PERSONAL CARE: Dark brown
- HOME CARE: Light green
- IMPULSE FOOD: Orange
- STAPLE FOOD: Blue
- MILK BASES: Yellow
- CIGARETTE: Pink
- BEVERAGE: Light blue
- BEER: Purple

### Stacked Bar Chart:
The stacked bar chart provides a detailed view of the FMCG categories by channels:
- FMCG dynamics – Value % Contribution
- FMCG dynamics – Value % Growth

The stacked bars are color-coded as follows:
- PERSONAL CARE: Dark brown
- HOME CARE: Light green
- IMPULSE FOOD: Orange
- STAPLE FOOD: Blue
- MILK BASES: Yellow
- CIGARETTE: Pink
- BEVERAGE: Light blue
- BEER: Purple

### Analysis:
1. **Value Contribution:**
   - PERSONAL CARE: 7.2%
   - HOME CARE: 5.9%
   - IMPULSE FOOD: 14.8%
   - STAPLE FOOD: 12.4%
   - MILK BASES: 19.4%
   - CIGARETTE: 6.2%
   - BEVERAGE: 8.0%
   - BEER: 22.1%

2. **Value Growth:**
   - PERSONAL CARE: 3.3%
   - HOME CARE: -2.0%
   - IMPULSE FOOD: -4.2%
   - STAPLE FOOD: 2.0%
   - MILK BASES: 1.4%
   - CIGARETTE: 6.2%
   - BEVERAGE: 4.2%
   - BEER: 8.0%

### Conclusion:
The image highlights that while the FMCG market as a whole shows growth, the personal care category is the most significant contributor, with a value contribution of 7.2%. The home care category shows the least contribution, with a value contribution of 5.9%. The stacked bar chart provides a clear view of the growth and contribution of each category by channels, with the beverage category showing the highest growth, contributing 8.0% to the overall value growth.

This detailed analysis provides marketers with insights into the FMCG market dynamics, highlighting the importance of personal care and the need to focus on growth in this category.
- Text Content: [IMAGE ANALYSIS]
The image is a comparative analysis of FMCG (Fast-Moving Consumer Goods) dynamics, focusing on the value contribution and growth across various categories and channels. The layout is divided into two main sections: a bar chart and a stacked bar chart.

### Bar Chart:
- **Title:** Beer, Cigarrete and Beverage drive the growth of FMCG in long term, while Personal Care & Home care are on decline as consumer's shift to online channels.
- **X-Axis:** Categories (Personal Care, Home Care, Impulse Food, Staple Food, Milk Bases, Cigarette, Beverage, Beer)
- **Y-Axis:** Value Contribution (%)
- **Values:**
  - Personal Care: 7.2
  - Home Care: 5.9
  - Impulse Food: 14.8
  - Staple Food: 12.4
  - Milk Bases: 19.4
  - Cigarette: 22.1
  - Beverage: 24.2
  - Beer: 22.1

### Stacked Bar Chart:
- **Title:** VN by channels – FMCG dynamics – Value % Contribution
- **X-Axis:** Categories (Personal Care, Home Care, Impulse Food, Staple Food, Milk Bases, Cigarette, Beverage, Beer)
- **Y-Axis:** Value Contribution (%)
- **Values:**
  - Personal Care: 6
  - Home Care: 5
  - Impulse Food: 10
  - Staple Food: 14
  - Milk Bases: 21
  - Cigarette: 21
  - Beverage: 24
  - Beer: 10

### Analysis:
1. **Beer, Cigarrete and Beverage:** These categories have the highest value contribution across all channels, indicating their significant impact on FMCG growth.
2. **Personal Care & Home Care:** These categories show a decline in value contribution, suggesting a shift in consumer behavior towards online channels.
3. **Impulse Food, Staple Food, Milk Bases, Cigarette, Beverage, Beer:** These categories show a mixed contribution, with some categories showing positive growth and others showing decline.

### Conclusion:
The image highlights the impact of consumer behavior shifts towards online channels on FMCG categories, particularly beer, cigarrete, and beverage. Personal care and home care categories show a decline in value contribution, indicating a shift towards online channels. The stacked bar chart provides a more detailed view of the contribution and growth across different categories and channels.


Page 10 Visual Data:
- Description: [IMAGE ANALYSIS]
This image is a comprehensive analysis of the Vietnam FMCG (Fast-Moving Consumer Goods) market, focusing on the value contribution and growth across various channels. The left side of the image presents a bar chart that compares the value contribution and growth of FMCG in Vietnam across different channels over the latest 12 months (12M) versus the previous year (12M YA). The channels include Semi-Retailer VN (Semi-retailers), Mom & Baby VN (Mom & Baby stores), Modern Trade VN (Modern Trade stores), Traditional Trade Off (Traditional trade outlets), and Traditional Trade On-Premise (Traditional trade on-premises).

The bar chart shows that the Modern Trade VN channel has the highest value contribution and growth, with a value of 52.4% and a growth rate of 11.0%. The Semi-Retailer VN channel has the lowest value contribution and growth, with a value of 15.0% and a growth rate of 14.8%. The Mom & Baby VN channel has a moderate value contribution and growth, with a value of 12.8% and a growth rate of 13.0%.

The right side of the image presents a table that lists the channels by their contribution to the FMCG universe stores. The table includes the following categories:
- FMCG
- Traditional Trade (OFF)
- Traditional Trade (ON-Premise)
- Modern Trade
- HRC (ON)
- HRC (OFF)

The table shows the percentage contribution of each channel type to the total number of stores in the FMCG universe. The FMCG channel has the highest contribution, with 1,242,927 stores, followed by Traditional Trade (OFF) with 1,124,927 stores, and Traditional Trade (ON-Premise) with 1,024,927 stores. The Modern Trade channel has the lowest contribution, with 1,024,927 stores.

Overall, the image highlights the growing importance of Modern Trade in the FMCG market in Vietnam, with a significant contribution and growth over the past year. The data suggests that Modern Trade stores are becoming more prevalent and influential in the FMCG market, indicating a shift towards more modern and efficient retailing practices.
- Text Content: [IMAGE ANALYSIS]
The image is a comparative analysis of the Vietnam FMCG (Fast-Moving Consumer Goods) market, focusing on the value contribution and growth across various channels. It includes two main sections: a bar chart and a table.

### Bar Chart:
The bar chart compares the value contribution and growth of FMCG in Vietnam across different channels over the latest 12 months (12M) and the previous 12 months (12M). The channels are categorized into three groups: Semi-Retailer VN (Semi-Retailer), Mom & Baby VN (Mom & Baby), and Modern Trade VN (Modern Trade).

- **Semi-Retailer VN**: 18.2% contribution and 1.4% growth.
- **Mom & Baby VN**: 12.8% contribution and 1.5% growth.
- **Modern Trade VN**: 52.5% contribution and 15.0% growth.

### Table:
The table on the right side of the image provides a breakdown of the FMCG market by channel type and their contribution to the total stores in the universe. The table includes the following categories:
- **FMCG**: 1,242,927 stores
- **Traditional Trade (OFF)**: 51% contribution
- **Traditional Trade (ON-Premise)**: 48% contribution
- **Modern Trade**: 1% contribution

### Analysis:
1. **Value Contribution**:
   - **Semi-Retailer VN**: 18.2% contribution.
   - **Mom & Baby VN**: 12.8% contribution.
   - **Modern Trade VN**: 52.5% contribution.

2. **Growth**:
   - **Semi-Retailer VN**: 1.4% growth.
   - **Mom & Baby VN**: 1.5% growth.
   - **Modern Trade VN**: 15.0% growth.

3. **Channel Type Contribution**:
   - **FMCG**: 1,242,927 stores.
   - **Traditional Trade (OFF)**: 51% contribution.
   - **Traditional Trade (ON-Premise)**: 48% contribution.
   - **Modern Trade**: 1% contribution.

### Conclusion:
The FMCG market in Vietnam has shown significant growth across all channels, with the Modern Trade channel contributing the most, followed by Semi-Retailer VN and Mom & Baby VN. The Traditional Trade (OFF) channel has the highest contribution, while the Traditional Trade (ON-Premise) channel has the lowest contribution. The Modern Trade channel, despite its small contribution, has shown significant growth over the past year.


Page 2 Visual Data:
- Description: [IMAGE ANALYSIS]
This image is a slide from a presentation, likely related to a company named SHS Research. The slide is titled "Mục Lục" which translates to "Table of Contents" in English. The slide contains a list of four main sections, each with a number and a brief description.

1. **01 TỔNG QUAN NGÀNH BÁN LÈ** - This section is labeled with the number 3 and is likely a brief overview of the company's overall business operations.
2. **02 TRIỂN VỌNG NGÀNH** - This section is labeled with the number 13 and is likely a detailed breakdown of the company's current business trends or initiatives.
3. **03 CẬP NHẬT DOANH NGHIỆP** - This section is labeled with the number 24 and is likely a summary of the company's recent business performance or achievements.
4. **04 PHỤ LỤC: CÂU CHUYÊN THÀNH CÔNG NƯỚC NGÀI** - This section is labeled with the number 30 and is likely a list of specific topics or areas of focus for the company.

The slide is designed to provide a quick overview of the company's main areas of focus and achievements. The use of numbers and brief descriptions helps to organize the information in a clear and concise manner.
- Text Content: [IMAGE ANALYSIS]
The image is a slide from a presentation, likely related to SHS Research, as indicated by the logo in the top right corner. The slide is titled "MỤC LỤC" which translates to "MOTIVATION" in Vietnamese. The slide contains a list of four categories, each with a corresponding number and a numerical value.

1. **01 TỔNG QUAN NGÀNH BÁN LÊ** (1)
   - **Value:** 3

2. **02 TRIỂN VỌNG NGÀNH** (2)
   - **Value:** 13

3. **03 CẬP NHẬT DOANH NGHIỆP** (3)
   - **Value:** 24

4. **04 PHỤ LỤC: CÂU CHUYÊN THÀNH CÔNG NƯỚC NGÀI** (4)
   - **Value:** 30

The slide layout is simple and straightforward, with each category listed in a horizontal format. The numbers are prominently displayed in white against a light background, making them easily readable. The categories are color-coded with orange for "01," blue for "02," and white for "03," and "04," with the last category in blue for "04."

At the bottom of the slide, there is a footer with the text "SHS Research | Báo cáo ngành bán lẻ" which translates to "SHS Research | Retail Industry Report." This indicates that the slide is part of a report or research document related to retail industry trends or performance metrics.

Overall, the slide provides a clear and concise overview of the key metrics or indicators for the SHS Research report, focusing on the retail industry.


Page 3 Visual Data:
- Description: [IMAGE ANALYSIS]
This image depicts the interior of a modern grocery store, showcasing a well-organized produce section. The store has a clean and modern design, with a focus on bright colors and a minimalist aesthetic. The produce section is filled with a variety of fruits and vegetables, including pumpkins, tomatoes, and other vegetables, arranged neatly on shelves and displays.

In the foreground, there is a person walking through the store, possibly browsing the produce. The store has a high ceiling with exposed beams, adding to the modern feel of the space. The lighting is bright and evenly distributed, ensuring that the produce is clearly visible.

On the left side of the image, there is a checkout counter where a cashier is working. The cashier is wearing a black uniform, and the counter is equipped with a cash register and a few other items. The cashier appears to be engaged in the process of serving a customer.

The right side of the image shows a section of the produce section, with a variety of pumpkins and other vegetables displayed on shelves. The pumpkins are arranged in a visually appealing manner, with some stacked on top of each other, creating a sense of depth and variety.

Overall, the image conveys a sense of modernity and convenience, with a focus on fresh produce and a well-organized shopping experience. The use of bright colors and a minimalist design contributes to a clean and inviting atmosphere.
- Text Content: [IMAGE ANALYSIS]
The image depicts the interior of a modern grocery store. The layout is well-organized, with a clean and spacious design. The store is brightly lit, with overhead lighting fixtures and natural light coming through large windows or skylights. The floor is made of polished stone or concrete, and the walls are painted in a neutral color, creating a bright and inviting atmosphere.

The store is divided into several sections, each containing various products. On the left side, there is a section with fresh produce, including vegetables and fruits. The produce section is well-stocked and organized, with different types of vegetables and fruits displayed on shelves and in bins. The produce is fresh and appears to be of high quality.

In the center of the store, there is a large display area with a variety of packaged goods, including canned goods, snacks, and other grocery items. The products are neatly arranged on shelves and in bins, making it easy for customers to find what they need.

On the right side of the store, there is a section with packaged goods, including meats, dairy products, and other grocery items. The products are also well-organized and displayed in a way that is easy for customers to navigate.

The store has a modern and sleek design, with clean lines and a minimalist aesthetic. The lighting is bright and even, with no harsh shadows or glare, making the store feel welcoming and comfortable. The overall atmosphere is one of convenience and convenience, with a focus on providing customers with a wide range of products in a clean and organized environment.


Page 4 Visual Data:
- Description: [IMAGE ANALYSIS]
This image is a detailed infographic from SHS Research, a Vietnamese company, showcasing their financial and economic projections for the years 2020 to 2025. The infographic is divided into several sections, each providing a specific piece of information related to the company's business and market trends.

### Top Section:
- **Title:** Tổng quan ngành bán lẻ (General Overview of Retail Industry)
- **Subtitle:** Tăng trưởng bán lẻ vs Tăng trưởng GDP (Growth of Retail vs GDP Growth)
- **Text:** Chi tiêu dùng đồ gốp lớn vào tăng trưởng, chiếm tỷ trọng trung bình 65% GDP hàng năm của Việt Nam. Sau giai đoạn 2020-2022 chịu ảnh hưởng bởi dịch Covid, doanh thu bán lẻ đang tăng trên đà hồi phục, dự kiến tăng trưởng 5,2% trong năm 2025, tương đương với tỷ lệ tăng trưởng +9,6% YoY.

### Middle Section:
- **Title:** Doanh thu bán lẻ hàng hóa và Dịch vụ Việt Nam (Retail Sales in Vietnam)
- **Bar Graph:** Shows the percentage of YoY GDP and YoY Sales for the years 2020 to 2025.
- **Text:** Doanh thu bán lẻ tăng trưởng 4,8% CAGR (Compound Annual Growth Rate) trong 9 năm từ 2020 đến 2025.

### Bottom Section:
- **Title:** Doanh thu bán lẻ hàng hóa và Dịch vụ (Retail Sales in Vietnam)
- **Bar Graph:** Shows the percentage of YoY Sales for the years 2014 to 2025.
- **Text:** Doanh thu bán lẻ tăng trưởng 9,6% YoY trong 9 năm từ 2014 đến 2025.

### Additional Information:
- **Source:** SHS Research
- **Note:** The infographic is from SHS Research, a Vietnamese company, and it provides a detailed overview of their financial and economic projections for the years 2020 to 2025.

### Analysis:
- **Retail Growth:** The infographic highlights the significant role of retail in the Vietnamese economy, with a 65% GDP share. The growth of retail is projected to be 5.2% in 2025, which is a positive sign for the Vietnamese retail sector.
- **Growth CAGR:** The compound annual growth rate (CAGR) for retail sales is 4.8%, indicating a steady and consistent growth over the 9-year period from 2020 to 2025.
- **Market Trends:** The infographic also shows that the retail market is expected to continue to grow, with a significant increase in sales from 2014 to 2025. This growth is projected to be 9.6% YoY, highlighting the robust demand for retail products and services in Vietnam.

Overall, this infographic provides valuable insights into the future growth prospects of the Vietnamese retail industry, highlighting the importance of retail in the Vietnamese economy and the expected positive growth trends over the next few years.
- Text Content: [IMAGE ANALYSIS]
The image is a slide from a presentation, likely related to economic or financial analysis, featuring various charts and data. The slide is titled "TỔNG QUAN NGÀNH BÁN LÈ" and includes several sections with different types of graphs and data visualizations.

### Title Section:
- The title at the top of the slide reads "TỔNG QUAN NGÀNH BÁN LÈ" which translates to "General Overview of Sales."

### Main Graphs:
1. **Tăng trưởng bán lẻ vs Tăng trưởng GDP:**
   - This graph compares the growth in sales (in blue) to the growth in GDP (in orange).
   - The x-axis represents years, and the y-axis represents percentages.
   - The graph shows a significant increase in sales growth compared to GDP growth, with sales growth peaking in 2022 and then declining slightly in 2023.

2. **Chi tiết dòng gốp lón vào tăng trưởng, chiếm tỷ trọng trung bình 65% GDP hàng năm của Việt Nam. Sau giai đoạn 2020-2022 chịu ảnh hưởng bởi dịch Covid, doanh thu bán lẻ đang tăng trưởng, lưỡng kế 9 tháng năm 2025 đạt gần 5,2, triều tỷ đồng, +9,6% YoY:**
   - This section provides additional context about the impact of the Covid-19 pandemic on Vietnam's economy.
   - It mentions that the average annual contribution of retail sales to GDP is 65%.
   - The slide notes that after the 2020-2022 period, retail sales have been growing, with a target of reaching around 5.2 trillion VND by the end of 2025, a 9.6% YoY growth.

3. **Doanh thu bán lẻ hàng hóa và Dịch vụ Việt Nam (ngính kỹ thuật):**
   - This graph shows the revenue from retail sales of goods and services in Vietnam.
   - The x-axis represents years, and the y-axis represents revenue in billion VND.
   - The graph shows a significant increase in revenue from retail sales, with a peak in 2022 and a slight decline in 2023.

4. **Doanh thu bán lẻ hàng hóa và Dịch vụ (ngính kỹ thuật):**
   - This graph shows the revenue from retail sales of goods and services in Vietnam.
   - The x-axis represents years, and the y-axis represents revenue in billion VND.
   - The graph shows a significant increase in revenue from retail sales, with a peak in 2022 and a slight decline in 2023.

### Additional Notes:
- The slide is from SHS Research, as indicated by the logo in the top right corner.
- The data is sourced from GSO.
- The CAGR (Compound Annual Growth Rate) is 4.8%.
- The revenue from retail sales is projected to grow by 9.6% annually.

### Analysis:
The slide provides a comprehensive overview of the growth in sales and revenue from retail sales in Vietnam, highlighting significant growth in both the short and long term. The data shows that despite the impact of the Covid-19 pandemic, retail sales have been growing, with a projected growth rate of 9.6% annually. This growth is expected to continue, with a peak in 2022 and a slight decline in 2023. The data also indicates that the revenue from retail sales is projected to grow by 9.6% annually, with a peak in 2022 and a slight decline in 2023.


Page 5 Visual Data:
- Description: [IMAGE ANALYSIS]
This image is a detailed infographic from SHS Research, focusing on the economic and market trends in Southeast Asia. The infographic is divided into several sections, each providing specific data and insights.

### Top Section: Total Market Size
- **Title:** Tổng quan ngành bán lẻ (Total Market Size)
- **Description:** The infographic highlights the total market size for retail in Southeast Asia, with a focus on the impact of various factors such as population growth, economic conditions, and technological advancements.
- **Data Points:**
  - **2022:** $134.0 billion
  - **2023e (Estimated):** $142.7 billion
  - **2024e (Estimated):** $154.0 billion
  - **2025f (Forecast):** $172.0 billion

### Middle Section: Share of Retail Sales by Sector
- **Title:** Cổ cảo chi tiêu dùng của hộ gia đình (%)
- **Description:** This section provides a breakdown of the share of retail sales by sector, including household consumption, food and beverages, and other categories.
- **Data Points:**
  - **2022:** 21.2%
  - **2023e (Estimated):** 15.0%
  - **2024e (Estimated):** 12.6%
  - **2025f (Forecast):** 12.2%

### Bottom Section: Share of Retail Sales by Country
- **Title:** Tỷ trọng chi tiêu dùng trong tổng chi tiêu dân gian tại các nước Châu Á (%)
- **Description:** This section provides a breakdown of the share of retail sales by country, including China, Indonesia, Japan, Malaysia, Philippines, Singapore, Thailand, and Vietnam.
- **Data Points:**
  - **China:** 6.5%
  - **Indonesia:** 5.2%
  - **Japan:** 3.0%
  - **Malaysia:** 2.6%
  - **Philippines:** 2.1%
  - **Singapore:** 1.8%
  - **Thailand:** 1.8%
  - **Vietnam:** 1.8%

### Footer Section: Source Information
- **Title:** SHS Research | Báo cáo ngành bán lẻ (SHS Research | Retail Industry Report)
- **Description:** The infographic is sourced from SHS Research, a reputable market research firm, and is part of their Retail Industry Report.

### Analysis:
- **Total Market Size:** The total market size for retail in Southeast Asia is projected to reach $172.0 billion by 2025, indicating a significant growth potential in the region.
- **Share of Retail Sales by Sector:** Household consumption is the largest segment, accounting for 21.2% of total retail sales. This highlights the importance of consumer behavior and household spending in the region.
- **Share of Retail Sales by Country:** China leads the way with a 6.5% share, followed by Indonesia with 5.2%. This indicates that China and Indonesia have a significant influence on the retail market in the region.
- **Technological Advancements:** The data suggests that technological advancements are driving consumer behavior and spending patterns, with a focus on e-commerce and digital retail.

Overall, this infographic provides a comprehensive overview of the retail market in Southeast Asia, highlighting key trends and insights that can inform business strategies and market analysis.
- Text Content: [IMAGE ANALYSIS]
The image is a page from a report titled "TỔNG QUAN NGÀNH BÁN LẺ" (Total Sales Sector). The report is from SHS Research, and it is part of a series of charts and graphs. The layout is divided into several sections, each containing different types of data and visualizations.

### Top Section:
- **Title**: "TỔNG QUAN NGÀNH BÁN LẺ"
- **Subtitle**: "SHS"
- **Graph**: This section contains a bar chart showing the total sales of various sectors in 2022 and projections for 2023 and 2024. The sectors are listed on the x-axis and the sales figures on the y-axis. The bars are color-coded, with blue for "Hàng hàng tiêu dùng" (Consumer goods) and purple for "Hàng hàng dịch vụ" (Service goods).

### Middle Section:
- **Title**: "CÔ CÁU CHI TIẾU DUNG CỦA HỘ GIA ĐỊNH (%)"
- **Subtitle**: "SHS"
- **Graph**: This section contains a bar chart showing the distribution of the total sales by different categories of goods. The categories are listed on the x-axis and the sales figures on the y-axis. The bars are color-coded, with blue for "Thực phẩm, đồ uống không còn" (Food, non-food products) and purple for "Nhà, tiện ích" (Houses, convenience stores).

### Bottom Section:
- **Title**: "TỔNG CHI TIẾU CHI TIẾU DUNG TẠI CÁC NƯỚC CHÂU Á (%)"
- **Subtitle**: "SHS"
- **Graph**: This section contains a bar chart showing the distribution of total sales by different regions in 2022 and projections for 2023 and 2024. The regions are listed on the x-axis and the sales figures on the y-axis. The bars are color-coded, with blue for "Trung Quốc" (China), orange for "Indonesia", red for "Thái Lan", yellow for "Singapore", green for "Philippines", and purple for "Thái Bình". The bars are labeled with the year of the data.

### Additional Information:
- **Source**: The report is from SHS Research.
- **Date**: The page number is 5.

### Analysis:
The report provides a comprehensive overview of the total sales and distribution of goods across different sectors and regions. The data is presented in a clear and organized manner, making it easy to understand the trends and patterns in the sales figures. The use of color-coding helps in distinguishing between different categories and regions, which is particularly useful for visual analysis. The data is sourced from SHS Research, a reputable company in the field of market research and analysis.