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

### Table Description

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

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

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

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

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

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

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

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

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

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

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

### Table Description:

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

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

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

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

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

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

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

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

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

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

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


Page 10 Visual Data:
- Description: [IMAGE ANALYSIS]
This image is a page from a research paper, 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.


[System] You are Project A, an expert Retail Consultant.

[User] Làm thế nào tôi có thể áp dụng số hóa và dịch vụ hóa để tăng cường khả năng cạnh tranh cho cửa hàng bán lẻ nhỏ của mình?

[Assistant]
<think>1. Start by identifying the core concepts from the text: digitalization (DG) and servitization (ST) are interdependent pillars essential for small independent retailers. 2. Recognize that Entrepreneurial Orientation (EO) and Entrepreneurial Competence (EC) drive DG and ST through innovation exploration (ER) and innovation exploitation (ET). 3. Note the finding that ET has a stronger effect than ER in promoting DG and ST. 4. Understand that DG contributes positively to ST, indicating they should be implemented together. 5. Consider that Perceived Value of Digital Servitization (PVDS) amplifies the impact of innovation on digitalization, while Competitive Pressure (CP) does not show significant moderation. 6. Based on this, formulate advice: focus on developing EO and EC, prioritize innovation exploitation, and treat DG and ST as complementary strategies while emphasizing the value of digital servitization.</think>
Dựa trên nghiên cứu, để áp dụng số hóa và dịch vụ hóa hiệu quả cho cửa hàng nhỏ của bạn, hãy: 1) Phát triển tinh thần doanh nhân và năng lực kinh doanh để thúc đẩy đổi mới sáng tạo; 2) Ưu tiên khai thác sáng tạo (như tối ưu hóa quy trình hiện có) hơn là chỉ khám phá sáng tạo mới; 3) Triển khai số hóa (ví dụ: công nghệ bán hàng trực tuyến) và dịch vụ hóa (như dịch vụ hỗ trợ khách hàng) song song vì chúng hỗ trợ lẫn nhau; 4) Tăng cường nhận thức về giá trị của số hóa dịch vụ để khuếch đại lợi ích. Áp lực cạnh tranh không phải yếu tố chính, nên tập trung vào cải thiện nội tại cửa hàng.


Page 10 Visual Data:
- Description: [IMAGE ANALYSIS]
This image appears to be a page from a research paper or academic article, specifically from a Vietnamese journal. The page number is 61, and the title of the section is "Bảng 4 Kiểm Định Giá Thuyết Nghĩa Cư." This translates to "Table 4: Determining the Meaning of the Price."

The table in the image is titled "Mỗi quan hệ," which means "Each relationship." It lists eight different relationships between variables, each with a corresponding coefficient (H1, H2, H3, etc.), a standardized coefficient (H1', H2', H3', etc.), a t-value (H1t, H2t, H3t, etc.), a p-value (H1p, H2p, H3p, etc.), and a significance level (H1σ, H2σ, H3σ, etc.).

The table is divided into two columns: "Mỗi quan hệ" (Each relationship) and "Hệ số tác động chuẩn hóa" (Standardized effect size). The coefficients are presented in the first column, and the standardized effect sizes are presented in the second column.

Below the table, there is a figure that represents the relationships between the variables. The figure is labeled "Hình 2 Kết Quả Kiểm Định Mô Hình" which translates to "Figure 2: Results of the Determination Model."

The figure shows a network diagram with arrows connecting the variables, indicating the direction of the relationships. The coefficients are represented by the lengths of the arrows, with longer arrows indicating stronger relationships.

The text at the bottom of the page mentions "Kết quả phân tích dữ liệu từ phần mềm SmartPLS," which translates to "Results of the analysis of data from the SmartPLS software."

The text also references "Hình 2 Kết Quả Kiểm Định Mô Hình," which translates to "Figure 2: Results of the Determination Model."

Overall, the image provides a detailed table and a figure that summarize the results of a statistical analysis using SmartPLS software. This suggests that the research is focused on understanding the relationships between different variables and determining the significance of those relationships.
- Text Content: [IMAGE ANALYSIS]
The image is a page from a document, specifically from a research paper. The page number is 61, and the title of the page is "Bảng 4 Kiểm Định Giá Thuyết Nghĩa Cư". The document appears to be in Vietnamese, as indicated by the text and the layout.

### Table Description:

#### Table Title:
- **Bảng 4 Kiểm Định Giá Thuyết Nghĩa Cư**

#### Columns:
1. **Giả thuyết**
2. **Môi quan hệ**
3. **Hệ số tác động chuẩn hoá**
4. **Hệ số tác động chuẩn hoá trung bình**
5. **Giá trị p-value**
6. **Kết quả**

#### Rows:
1. **H1**
   - **Cả nhân hóa -> Lo ngại về quyền riêng tư**
   - **0.289**
   - **0.290**
   - **0.000**
   - **Chấp nhận**
2. **H2**
   - **Cả nhân hóa -> Tính hủu ích**
   - **0.443**
   - **0.447**
   - **0.000**
   - **Chấp nhận**
3. **H3**
   - **Cả nhân hóa -> Đề sử dụng**
   - **0.248**
   - **0.247**
   - **0.001**
   - **Chấp nhận**
4. **H4**
   - **Niềm tin năng lực -> Tính hủu ích**
   - **0.251**
   - **0.245**
   - **0.001**
   - **Chấp nhận**
5. **H5**
   - **Niềm tin năng lực -> Đề sử dụng**
   - **0.562**
   - **0.560**
   - **0.000**
   - **Chấp nhận**
6. **H6**
   - **Lo ngại về quyền riêng tư -> Y định sử dụng**
   - **-0.050**
   - **-0.049**
   - **0.365**
   - **Bác bỏ**
7. **H7**
   - **Tính hủu ích -> Y định sử dụng**
   - **0.457**
   - **0.455**
   - **0.000**
   - **Chấp nhận**
8. **H8**
   - **Đề sử dụng -> Y định sử dụng**
   - **0.376**
   - **0.374**
   - **0.000**
   - **Chấp nhận**

### Graph Description:

#### Graph Title:
- **Hình 2 Kết Quả Kiểm Định Mô Hình**

#### Graph:
- **LO LÀNG QUYỀN RIÊNG TƯ**
- **CÁ NHÂN HÓA**
- **TÍNH HỦU ICH**
- **Y ĐỊNH MUA**
- **NIEM TIN NĂNG LỰC**
- **ĐỀ SỨ ĐỤNG**

#### Graph Elements:
- **Nodes (Circles):**
  - **Cá nhân hóa**
  - **Tính hủu ích**
  - **Y định sử dụng**
  - **Niềm tin năng lực**
  - **Đề sử dụng**
- **Edges (Lines):**
  - **Cá nhân hóa -> Tính hủu ích**
  - **Cá nhân hóa -> Đề sử dụng**
  - **Tính hủu ích -> Y định sử dụng**
  - **Niềm tin năng lực -> Tính hủu ích**
  - **Niềm tin năng lực -> Đề sử dụng**
  - **Đề sử dụng -> Y định sử dụng**

### Analysis:

The table and graph provide a structured way to present the results of a statistical analysis. The table lists the hypotheses (H1-H8) and their corresponding coefficients, standardised coefficients, and p-values. The graph visualises the relationships between the variables, with nodes representing variables and edges representing the relationships between them.

### Conclusion:

The document appears to be a part of a research paper that examines the relationships between various factors and their impact on a specific outcome. The table and graph provide a clear and concise way to present the findings, making it easier for readers to understand the results and the relationships between the variables.


[System] You are Project A, an expert Data Analyst.

[User] Tốc độ tăng trưởng GDP và tiêu dùng trong quý I năm 2025 cho thấy điều gì về cơ hội cho cửa hàng bán lẻ của tôi?

[Assistant]
<think>First, I extracted key data from the provided OCR text: GDP growth in Q1 2025 is 7.70% compared to the same period last year, with the services sector leading at 7.70%, while agriculture and industry grew at 3.50% and 3.74%, respectively. Additionally, consumption increased by 10.29% year-over-year. The key insight is that the Vietnamese economy is experiencing robust growth, driven by services and strong consumer spending. For a store owner, this suggests a favorable environment with higher economic activity and consumer confidence, which can boost retail sales. I then formulated a relevant question in Vietnamese and prepared an answer citing specific trends from the graph.</think>
Dựa trên biểu đồ từ báo cáo, GDP quý I năm 2025 tăng 7.70% so với cùng kỳ năm trước, với ngành dịch vụ tăng mạnh nhất ở mức 7.70%. Điều này cho thấy nền kinh tế đang phục hồi nhanh chóng, kết hợp với mức tiêu dùng tăng 10.29%, báo hiệu cơ hội tốt cho cửa hàng của bạn: người tiêu dùng có xu hướng chi tiêu nhiều hơn, có thể dẫn đến tăng doanh số bán lẻ. Bạn nên tập trung vào các mặt hàng liên quan đến dịch vụ và nhu cầu tiêu dùng để tận dụng xu hướng này.


Page 9 Visual Data:
- Description: [IMAGE ANALYSIS]
This image is a pie chart from SHS Research, which provides a breakdown of the total number of stores by category. The chart is titled "Tổng Quan Ngành Bán Lẻ" (Total Overview of Retail Sector) and includes the logo of SHS Research at the top right corner.

### Breakdown of the Pie Chart:
1. **Pharmacy (Pharmacy)**
   - **Total Stores**: 1,614
   - **Share**: 25%

2. **Electronics (Electronics)**
   - **Total Stores**: 1,283
   - **Share**: 20%

3. **Media Mart**
   - **Total Stores**: 985
   - **Share**: 15%

4. **Viettel Store**
   - **Total Stores**: 735
   - **Share**: 11%

5. **Nha Thuoc Long Chau**
   - **Total Stores**: 69
   - **Share**: 1%

6. **Nha Thuoc Pharmacy**
   - **Total Stores**: 526
   - **Share**: 8%

7. **FPT Shop**
   - **Total Stores**: 421
   - **Share**: 6%

8. **FPT Retail**
   - **Total Stores**: 349
   - **Share**: 5%

9. **The Gioididong**
   - **Total Stores**: 316
   - **Share**: 5%

### Additional Information:
- The chart is sourced from SHS Research and is titled "Báo cáo ngành bán lẻ" (Retail Sector Report).
- The logo of SHS Research is prominently displayed at the top right corner of the chart.

### Analysis:
- The pharmacy category has the highest number of stores (1,614), followed by electronics (1,283).
- Media Mart and Viettel Store have the highest shares (15% and 11%, respectively), indicating they have the most stores among the listed categories.
- The remaining categories have significantly lower shares, with Nha Thuoc Long Chau having the lowest share (1%).

### Marketing Implications:
- SHS Research's chart provides valuable insights into the distribution of retail stores across different categories. This information can be used by businesses to understand their market share and identify areas for growth or optimization.
- The high shares of Media Mart and Viettel Store suggest they are well-established and may be targets for expansion or strategic investments.
- The lower shares of Nha Thuoc Long Chau and Nha Thuoc Pharmacy indicate they may need to focus on increasing their market share or diversify their offerings.

Overall, this chart is a useful tool for businesses looking to understand their retail market position and identify areas for strategic growth.
- Text Content: [IMAGE ANALYSIS]
The image is a pie chart from SHS Research, detailing the total number of stores by category. The chart is divided into three main categories: Pharmacy, Electronics, and Media Mart. Each category is represented by a pie slice, with the total number of stores for each category shown in the legend at the bottom of the chart.

### Pie Chart Breakdown:
1. **Pharmacy**:
   - **Total Stores**: 1,614
   - **Pie Slice**: 25% (yellow)

2. **Electronics**:
   - **Total Stores**: 1,128
   - **Pie Slice**: 18% (orange)

3. **Media Mart**:
   - **Total Stores**: 985
   - **Pie Slice**: 14% (pink)

### Legend:
- **Pharmacy**: Yellow
- **Electronics**: Orange
- **Media Mart**: Pink

### Additional Information:
- The source of the data is SHS Research.
- The chart is titled "Tổng Quan ngành bán lẻ" which translates to "Total Overview of Retail Industry."

### Analysis:
- The Pharmacy category has the highest number of stores, with 1,614 stores.
- The Electronics category has the second highest number of stores, with 1,128 stores.
- The Media Mart category has the lowest number of stores, with 985 stores.

### Relevant Knowledge:
Retail industry data often includes categories like "Pharmacy," "Electronics," and "Media Mart" to provide a comprehensive view of the market. The total number of stores for each category gives an idea of the distribution of retail outlets across different sectors.

### Conclusion:
The pie chart provides a clear and concise overview of the total number of stores across different categories, which can be useful for market analysis and strategic planning.


[System] You are Project A, an expert Retail Consultant.

[User] Làm thế nào để cửa hàng nhỏ của tôi có thể cạnh tranh với các nhà bán lẻ lớn như Vincom và sự bùng nổ của mua sắm trực tuyến?

[Assistant]
<think>1. First, identify the user's concern: A small store owner wants to compete with large retailers and adapt to e-commerce trends. 2. Refer to the source document: It states that traditional retail (like markets and small stores) is losing market share, with modern retail increasing from 15% in 2015 to 26% in 2022. E-commerce is booming, with Vietnam having one of the fastest growth rates (CAGR 12.3% from 2023-2027). Large retailers like Vincom and Aeon are expanding aggressively by increasing floor area to gain market share. 3. Infer strategies: Since small stores cannot compete on scale, they should leverage their local advantages. The text shows e-commerce growth is high, so integrating online sales could be beneficial. Traditional retail still holds a significant portion, so maintaining quality service and convenience might help. Suggest focusing on niche markets or enhancing customer experience to differentiate from large chains. 4. Base the response on these trends: Emphasize adapting by going online, improving in-store offerings, and staying agile in a competitive market.</think>
Dựa trên xu hướng thị trường, bạn có thể cạnh tranh bằng cách: 1) Khai thác thương mại điện tử: Việt Nam có tốc độ tăng trưởng TMĐT cao (CAGR 12.3% từ 2023-2027), vì vậy hãy xây dựng kênh bán hàng trực tuyến để tiếp cận khách hàng rộng hơn. 2) Tập trung vào điểm mạnh địa phương: Các cửa hàng nhỏ có thể cung cấp dịch vụ cá nhân hóa và tiện lợi, trong khi các đại gia như Vincom đầu tư mở rộng diện tích (ví dụ: Vincom có 1.747 triệu m²). 3) Thích ứng linh hoạt: Thị phần bán lẻ hiện đại đã tăng từ 15% lên 26% (2015-2022), nên cân bằng giữa duy trì kênh truyền thống và áp dụng công nghệ để cải thiện trải nghiệm khách hàng. Chú trọng vào chất lượng và sự khác biệt để tồn tại trong thị trường cạnh tranh gay gắt.


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 7 Visual Data:
- Description: [IMAGE ANALYSIS]
This image is a bar chart titled "Hình 3: Vốn đầu tư nước ngoài đang ký vào Việt Nam tháng 5 các năm 2021-2025 (Tỷ USD) - Người GSO". The chart shows the investment from foreign investors into Vietnam in the months of May from 2021 to 2025 in USD (billion USD).

### Description of the Chart:
1. **Title and Axes:**
   - The title of the chart is "Hình 3: Vốn đầu tư nước ngoài đang ký vào Việt Nam tháng 5 các năm 2021-2025 (Tỷ USD) - Người GSO".
   - The x-axis represents the years from 2021 to 2025.
   - The y-axis represents the investment in USD (billion USD).

2. **Bars:**
   - There are three bars for each year from 2021 to 2025.
   - The bars are color-coded:
     - Blue for "Đăng ký cấp mới"
     - Orange for "Đăng ký điều chỉnh"
     - Green for "Gấp vốn, mua cổ phần"

3. **Data Points:**
   - **2021:**
     - "Đăng ký cấp mới": 8.83 billion USD
     - "Đăng ký điều chỉnh": 3.86 billion USD
     - "Gấp vốn, mua cổ phần": 1.31 billion USD
   - **2022:**
     - "Đăng ký cấp mới": 4.12 billion USD
     - "Đăng ký điều chỉnh": 1.98 billion USD
     - "Gấp vốn, mua cổ phần": 1.31 billion USD
   - **2023:**
     - "Đăng ký cấp mới": 5.26 billion USD
     - "Đăng ký điều chỉnh": 3.32 billion USD
     - "Gấp vốn, mua cổ phần": 1.98 billion USD
   - **2024:**
     - "Đăng ký cấp mới": 8.08 billion USD
     - "Đăng ký điều chỉnh": 2.52 billion USD
     - "Gấp vốn, mua cổ phần": 1.56 billion USD
   - **2025:**
     - "Đăng ký cấp mới": 7.02 billion USD
     - "Đăng ký điều chỉnh": 2.85 billion USD
     - "Gấp vốn, mua cổ phần": 1.56 billion USD

### Analysis:
- **2021-2022:**
  - The investment in "Đăng ký cấp mới" (new registrations) has increased significantly, from 8.83 billion USD in 2021 to 4.12 billion USD in 2022.
  - The investment in "Đăng ký điều chỉnh" (adjustment registrations) has also increased, from 3.86 billion USD in 2021 to 1.98 billion USD in 2022.
  - The investment in "Gấp vốn, mua cổ phần" (capital increase, buying shares) has remained relatively stable, from 1.31 billion USD in 2021 to 1.31 billion USD in 2022.

- **2023-2025:**
  - The investment in "Đăng ký cấp mới" has decreased slightly, from 5.26 billion USD in 2023 to 5.26 billion USD in 2024.
  - The investment in "Đăng ký điều chỉnh" has decreased significantly, from 3.32 billion USD in 2023 to 2.85 billion USD in 2024.
  - The investment in "Gấp vốn, mua cổ phần" has remained relatively stable, from 1.98 billion USD in 2023 to 1.98 billion USD in 2024.

### Conclusion:
The chart shows a general trend of increasing investment in new registrations and capital increase, with a slight decrease in adjustment registrations. The investment in "Gop vón, mua cổ phần" (capital increase, buying shares) has remained relatively stable over the years. This indicates a growing trend in foreign investment in Vietnam, particularly in the areas of new registrations and capital increase.
- Text Content: [IMAGE ANALYSIS]
The image is a page from a document that contains both textual content and a bar chart. The layout is as follows:

### Textual Content
The text is divided into several paragraphs, each discussing economic and business-related topics. The paragraphs are organized in a logical sequence, providing a comprehensive overview of the subject matter. The text is written in Vietnamese and appears to be informative, possibly discussing economic trends, market analysis, or business strategies.

### Bar Chart
The bar chart is located at the top of the page and is divided into four sections, each representing a different category of data. The categories are:

1. **2025**
   - **Đăng ký cấp mới**: 7,02 tỷ USD
   - **Đăng ký điều chỉnh**: 8,52 tỷ USD
   - **Gấp vốn, mua cơ sở**: 2,85 tỷ USD
   - **18,39 tỷ USD**

2. **2024**
   - **Đăng ký cấp mới**: 8,08 tỷ USD
   - **Đăng ký điều chỉnh**: 2,52 tỷ USD
   - **Gấp vốn, mua cơ sở**: 1,56 tỷ USD
   - **12,16 tỷ USD**

3. **2023**
   - **Đăng ký cấp mới**: 5,26 tỷ USD
   - **Đăng ký điều chỉnh**: 2,28 tỷ USD
   - **Gấp vốn, mua cơ sở**: 3,32 tỷ USD
   - **10,86 tỷ USD**

4. **2022**
   - **Đăng ký cấp mới**: 4,12 tỷ USD
   - **Đăng ký điều chỉnh**: 5,61 tỷ USD
   - **Gấp vốn, mua cơ sở**: 1,98 tỷ USD
   - **11,71 tỷ USD**

### Analysis
The bar chart provides a visual representation of the data for each year from 2021 to 2025. The values are in billions of USD, and the categories are clearly labeled. The data shows a gradual increase in the amount of foreign direct investment (FDI) over the years, with the highest amount in 2025 at 18.39 billion USD. The data for 2024 and 2023 are also significant, with the highest values in 2025.

### Relevant Knowledge
FDI is a significant factor in economic growth and development. It involves foreign investors investing in a country's economy, typically through the establishment of new businesses or the acquisition of existing businesses. The increase in FDI in Vietnam from 2021 to 2025 indicates a growing foreign presence in the country, which could be attributed to various factors such as economic reforms, improved infrastructure, and a favorable business environment.

### Conclusion
The document provides a detailed analysis of the foreign investment trends in Vietnam over the specified years, with a focus on the growth and distribution of FDI. The bar chart serves as a visual representation of this data, highlighting the significant increase in FDI over the period. The text accompanying the chart provides additional context and analysis, offering insights into the economic and business strategies that have contributed to this growth.


Page 5 Visual Data:
- Description: [IMAGE ANALYSIS]
This image is a comprehensive analysis of a company's business projections for the years 2020 to 2025. The image is divided into four main sections, each depicting different aspects of the company's revenue and growth projections.

### 1. **Revenue and Growth Projections**
- **Bar Chart:** The top left section shows the revenue projections for the years 2020 to 2025F (future years). The revenue is presented in USD.
- **Line Chart:** The top right section displays the revenue growth rate from 2020 to 2025F. The growth rate is shown as a percentage.

### 2. **Tang Truong Thu Nhap/Dau Nguoi Va Lam Phat Giai Doan**
- **Line Chart:** The bottom left section shows the tang truong (growth) of the revenue and the tang du nhat tin dung (growth of the total number of customers).
- **Line Chart:** The bottom right section displays the tang du nhat tin dung (growth of the total number of customers) over the years 2019 to 2024.

### 3. **Tang Truong Thu Nhap/Chu Nguoi Va Lam Phat Giai Doan**
- **Line Chart:** The middle left section shows the tang truong (growth) of the revenue and the tang du nhat tin dung (growth of the total number of customers).
- **Line Chart:** The middle right section displays the tang du nhat tin dung (growth of the total number of customers) over the years 2019 to 2024.

### 4. **Dung Tin Dung Giai Doan 2019-2024**
- **Bar Chart:** The bottom right section shows the total number of customers over the years 2019 to 2024.
- **Bar Chart:** The middle right section shows the total number of customers over the years 2019 to 2024.

### Analysis:
- **Revenue Growth:** The revenue projections show a gradual increase from 2020 to 2025F, with a slight dip in 2022 and 2023F. The revenue growth rate is projected to be around 3.20% to 3.50%.
- **Customer Growth:** The customer growth projections show a steady increase from 2019 to 2024, with a slight decline in 2022 and 2023F. The customer growth rate is projected to be around 13.6% to 14.2%.
- **Total Number of Customers:** The total number of customers is projected to increase from 2019 to 2024, with a slight decline in 2022 and 2023F. The total number of customers is projected to be around 13,600 to 14,200.

### Conclusion:
The image provides a detailed analysis of the company's revenue and customer growth projections for the years 2020 to 2025F. The revenue growth is projected to be steady, with a slight decline in 2022 and 2023F. The customer growth is also projected to be steady, with a slight decline in 2022 and 2023F. The total number of customers is projected to increase steadily, with a slight decline in 2022 and 2023F.
- Text Content: [IMAGE ANALYSIS]
The image is a slide from a presentation, likely related to economic or financial analysis. The slide is divided into several sections, each containing different types of graphs and data. Here is a detailed description of each section:

### Title Section
- **Title**: NGÀNH BÁN LÉ NĂM 2025 TIẾP ĐÀ TĂNG TRƯỜNG (tiếp)
- **Subtitle**: ABS (Abbott Building Services)

### Graphs and Data
#### 1. **Bar Graph (2020-2025F)**:
- **Title**: Thu nhập bình quân đầu người giai đoạn 2020-2025F (ngính USD)
- **Axes**:
  - **X-axis**: Years (2020, 2021, 2022, 2023, 2024F, 2025F)
  - **Y-axis**: USD
- **Bars**: Represents the total revenue for each year.
  - **2020**: 3.55 USD
  - **2021**: 3.76 USD
  - **2022**: 4.10 USD
  - **2023**: 4.32 USD
  - **2024F**: 4.65 USD
  - **2025F**: 4.90 USD

#### 2. **Line Graph (2020-2025F)**:
- **Title**: Tỷ lệ thất nghiệp giai đoạn 2020-2025F
- **Axes**:
  - **X-axis**: Years (2020, 2021, 2022, 2023, 2024, 2025F)
  - **Y-axis**: Percentage
- **Lines**: Represents the percentage of unemployment over time.

#### 3. **Line Graph (2020-2025F)**:
- **Title**: Tăng trưởng thu nhập/đầu người và làm phát giai đoạn 2020-2025F
- **Axes**:
  - **X-axis**: Years (2020, 2021, 2022, 2023, 2024F, 2025F)
  - **Y-axis**: Percentage
- **Lines**: Represents the percentage of growth in income and employment over time.

#### 4. **Bar Graph (2019-2024)**:
- **Title**: Dự báo tín dụng giai đoạn 2019-2024
- **Axes**:
  - **X-axis**: Years (2019, 2020, 2021, 2022, 2023, 2024)
  - **Y-axis**: Percentage
- **Bars**: Represents the percentage of credit demand over time.

### Footer
- **Source**: GSO, IMF, ABS Research

### Analysis
The slide provides a comprehensive overview of economic trends and projections for the years 2020-2025F. The bar graph shows the total revenue for each year, indicating a gradual increase over time. The line graphs depict the percentage of unemployment and the percentage of growth in income and employment, showing a fluctuating trend with some periods of decline and growth.

### Conclusion
The slide is a detailed analysis of economic trends and projections, providing insights into the future of the industry. The data presented is crucial for stakeholders in the industry to make informed decisions and plan for future growth.


[System] You are Project A, an expert Retail Consultant.

[User] Là chủ cửa hàng bán lẻ tại Việt Nam, tôi muốn biết cách nghiên cứu khả năng chấp nhận SST từ khách hàng trước khi đầu tư vào hệ thống tự thanh toán.

[Assistant]
<think>The user is a Vietnamese store owner concerned about customer acceptance of SST before investment. Based on the source document, SST acceptance is uncertain, especially in developing countries like Vietnam, and factors such as technology anxiety, perceived ease of use, usefulness, reliability, and risk influence it. To solve this, I should guide them to conduct pre-implementation research. Steps: 1) Emphasize the need for local research, as highlighted in the text (e.g., Azam & ctg., 2023). 2) Refer to studies like Ngadiman (2022) that show demographic and personal factors affect SST use, but suggest expanding to include cognitive factors like perceived ease of use and usefulness. 3) Recommend practical methods: survey customers on key factors, analyze data, and consider pilot testing to reduce risks. 4) Highlight the importance of understanding consumer needs to ensure the technology is appealing, as not all SSTs are universally attractive (Bulmer & ctg., 2018).</think>
Dựa trên nghiên cứu, để đánh giá khả năng chấp nhận SST, bạn nên tiến hành khảo sát khách hàng trước khi đầu tư. Tập trung vào các yếu tố như lo lắng về công nghệ, cảm nhận về độ dễ sử dụng, hữu ích, độ tin cậy và rủi ro, như được đề cập trong các nghiên cứu (ví dụ: Ngadiman, 2022). Nên xem xét đặc điểm nhân khẩu học và bối cảnh địa phương, vì sự chấp nhận có thể khác ở các nước đang phát triển như Việt Nam. Thử nghiệm nhỏ với một nhóm khách hàng có thể giúp giảm chi phí và rủi ro, đồng thời khám phá nhu cầu thực tế để đảm bảo SST phù hợp với cửa hàng của bạn.


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


[System] You are Project A, an expert Retail Consultant.

[User] Làm thế nào tôi, một chủ cửa hàng bán lẻ tại Việt Nam, có thể áp dụng trí tuệ nhân tạo để dự báo hiệu quả tài chính như ROA và ROE?

[Assistant]
<think>Based on the source document, which applies AI models to forecast ROA and ROE for retail enterprises in Vietnam, the solution involves: 1. Identifying the need to predict financial performance for better business decisions. 2. Referring to the study's method: collecting financial data from 12 retail enterprises (2010-2024) and macroeconomic variables (CPI, exchange rates, gold and oil prices). 3. Applying AI models like Random Forest, XGBoost, or MLP, with Random Forest showing the highest accuracy. 4. Guiding the store owner to gather similar data for their store and use the recommended model to train and make predictions.</think>
Bạn có thể áp dụng trí tuệ nhân tạo bằng cách thu thập dữ liệu tài chính lịch sử của cửa hàng (ví dụ: doanh thu, chi phí) và kết hợp với các biến kinh tế vĩ mô như CPI, tỷ giá, giá vàng, và giá dầu. Nghiên cứu cho thấy mô hình Random Forest đạt độ chính xác cao nhất trong dự báo ROA và ROE. Bạn nên sử dụng công cụ AI này để phân tích dữ liệu, dự báo các chỉ số tài chính, từ đó điều chỉnh chiến lược kinh doanh và cải thiện quyết định tài chính.


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

The content of the page is as follows:

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

**2.3. Các khái niệm liên quan**

**2.3.1. Cả nhân hóa**

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

**2.3.2. Lo ngại về quyền riêng tư**

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

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

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

**2.4. Phát triển các giải thích**

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

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

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

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

---

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


[System] You are Project A, an expert Data Analyst.

[User] Xu hướng doanh thu bán lẻ hàng hóa ở Việt Nam như thế nào từ năm 2020 đến 2024, và dự báo tăng trưởng cho năm 2025 là bao nhiêu?

[Assistant]
<think>First, I analyzed the OCR text from the visual data. It contains Vietnamese text with some errors, but key elements can be extracted. The data includes percentages like 78.4%, 81.2%, etc., which likely represent the contribution of retail goods sales to total retail and services over time. Specific sales figures are mentioned, such as '435.7 nghin ti dong' for December 2024 with 9.90% YoY growth, and a forecast of '5,388 nghểng nững nam 2025' with 9.95% YoY growth. Years are indicated from 2020 to 2024, with projections for 2025. The trend shows consistent high contribution percentages (mostly above 75%) and positive year-over-year growth, indicating a strong and growing retail market in Vietnam. This data can answer a store owner's question about market trends and future expectations.</think>
Dựa trên biểu đồ từ báo cáo, doanh thu bán lẻ hàng hóa ở Việt Nam có xu hướng tăng trưởng ổn định và đóng góp lớn vào tổng doanh thu bán lẻ và dịch vụ. Từ năm 2020 đến 2024, tỷ trọng đóng góp thường dao động trên 75%, cho thấy sức mua mạnh mẽ. Cụ thể, tháng 12/2024 ước tính đạt 435.7 nghìn tỷ đồng, tăng 9.90% so với cùng kỳ năm trước. Dự báo cho năm 2025 là doanh thu đạt khoảng 5,388 nghìn tỷ đồng, với mức tăng trưởng 9.95% so với năm 2024, phản ánh triển vọng tích cực cho ngành bán lẻ.


[System] You are Project A, an expert Data Analyst.

[User] Các chỉ số trong bảng này, như Cronbach's Alpha và AVE, có ý nghĩa gì đối với việc đo lường các yếu tố như định hướng đổi mới và giá trị cảm nhận trong cửa hàng bán lẻ của tôi?

[Assistant]
<think>First, I analyzed the provided OCR data from the Vietnam Retail Report, which includes tables (Bảng 2 and Bảng 3) with statistical measures like Cronbach's Alpha, CR (Composite Reliability), AVE (Average Variance Extracted), and HTMT (Heterotrait-Monotrait Ratio). These are commonly used in research to validate measurement scales. Key values: Cronbach's Alpha for factors like EO (Entrepreneurial Orientation) is 0.891, CR is 0.927, AVE is 0.808, all indicating high reliability and convergent validity (typically, Alpha > 0.7 and AVE > 0.5 are acceptable). HTMT ratios in Bảng 3 show discriminant validity, with most values below 0.85, suggesting distinct constructs. The business insight is that the scales for EO and perceived value dimensions (e.g., knowledge, emotional, social value) are statistically valid and reliable, meaning store owners can confidently use similar metrics to assess and improve their business practices, such as innovation orientation and customer value perception. For the response, I'll address the user's query by explaining how these indices demonstrate reliability and validity, citing specific trends like high Alpha and AVE scores.</think>
Dựa trên bảng dữ liệu từ báo cáo bán lẻ Việt Nam, các chỉ số Cronbach's Alpha (ví dụ: 0.891 cho Định hướng đổi mới) và AVE (ví dụ: 0.808) đều vượt ngưỡng tiêu chuẩn (Alpha > 0.7, AVE > 0.5), cho thấy các thang đo này có độ tin cậy cao và giá trị hội tụ tốt. Điều này có nghĩa là bạn có thể sử dụng các chỉ số tương tự, như định hướng đổi mới (EO) và các chiều kích giá trị cảm nhận (ví dụ: giá trị tri thức, giá trị cảm xúc), để đánh giá chính xác hiệu quả kinh doanh trong cửa hàng của mình. Xu hướng từ bảng cho thấy các yếu tố này được đo lường một cách đáng tin cậy, giúp bạn tập trung cải thiện các khía cạnh then chốt như đổi mới và tăng cường giá trị cho khách hàng.


Page 10 Visual Data:
- Description: [IMAGE ANALYSIS]
This image is a table from a financial report, specifically from ABS Research, detailing the financial projections for three companies: MWG, FRT, and PNJ. The table is structured with columns for different financial metrics for each company in the years 2023, 2024F (first half of 2024), and 2025F (second half of 2025). The table includes data on revenue, profit, and other financial metrics for each company.

### Table Description:

#### Table Title:
- **CÔ PHIỀU KHUYẾN NGHIỆT - MWG, FRT, PNJ**

#### Company Information:
- **ABS Research**
- **Trồng Vệ Trái Nghĩa Mở Đầu Tư**

#### Financial Metrics:
- **Doanh thu (Revenue):**
  - MWG: 118.280, 130.499, 143.549, 31.850, 38.764, 42.640
  - FRT: 27.120, 31.410, 5.162, 7.249, 8.396, 6.059
  - PNJ: 22.521, 27.120, 31.410, 5.162, 7.249, 6.868

- **%YoY (Year-over-Year):**
  - MWG: (11.3%), 10.3%, 10%, 5.6%, 21.7%, 10%
  - FRT: (2.2%), 16.5%, 16.5%, 10%, (2.2%), -3.9%
  - PNJ: (96%), 2.084%, 21.0%, NA, 6.5%, 13.8%

- **LNG (Natural Gas):**
  - MWG: 22.521, 27.120, 31.410, 5.162, 7.249, 6.059
  - FRT: 6.059, 6.758, 6.868, 8.396, 8.396, 6.868
  - PNJ: 6.868, 6.868, 6.868, 6.868, 6.868, 6.868

- **Biên LNG (%):**
  - MWG: 20%, 20.8%, 21.9%, 16.2%, 18.7%, 18.5%
  - FRT: 17.5%, 18.3%, 19.7%, 18.7%, 18.7%, 18.5%
  - PNJ: 18.5%, 18.5%, 18.5%, 18.5%, 18.5%, 18.5%

- **LNST Công ty mẹ (Natural Gas Sales to the Company):**
  - MWG: 168, 3.656, 4.427, (346), 1.971, 2.100
  - FRT: 320, 4.427, 601, 601, 2.100, 2.389
  - PNJ: 601, 601, 601, 601, 601, 601

- **%YoY (Year-over-Year):**
  - MWG: (96%), 2.084%, 21.0%, NA, 87.8%, 13.8%
  - FRT: (96%), 2.084%, 21.0%, NA, 87.8%, 13.8%
  - PNJ: (96%), 2.084%, 21.0%, NA, 87.8%, 13.8%

- **EPS (Earnings Per Share):**
  - MWG: 115, 2.500, 3.027, -2.5
- Text Content: [IMAGE ANALYSIS]
The image is a table from a financial report, specifically from ABS Research. The table is titled "CÔ PHIỀU KHUYẾN NGHIỆT - MWG, FRT, PNJ" which translates to "Sales Forecast - MWG, FRT, PNJ." The table is divided into two main sections: the top section contains the title and some introductory text, while the bottom section contains the actual data for each company (MWG, FRT, PNJ) for the years 2023, 2024F (first half of 2024), and 2025F (second half of 2025).

### Table Description:

#### Title:
- CÔ PHIỀU KHUYẾN NGHIỆT - MWG, FRT, PNJ

#### Company Information:
- The table lists three companies: MWG, FRT, and PNJ.

#### Data for Each Company:
- **2023:**
  - Doanh thu (Sales): 118,280
  - %YoY (Year-over-Year Growth): (11,3%)
  - LNG (Natural Gas): 22,521
  - Biên LNG (%): 20%
  - LNST Công ty mẹ (Natural Gas Sales): 168
  - %YoY (Year-over-Year Growth): (96%)
  - EPS (Earnings Per Share): 115
  - BVPS (Book Value Per Share): 15.954
  - Nợ/VCSH (lần): 1,1
  - ROA (Return on Assets): 0,3%
  - ROE (Return on Equity): 0,7%

- **2024F:**
  - Doanh thu (Sales): 130,499
  - %YoY (Year-over-Year Growth): (10,3%)
  - LNG (Natural Gas): 27,120
  - Biên LNG (%): 20,8%
  - LNST Công ty mẹ (Natural Gas Sales): 3.656
  - %YoY (Year-over-Year Growth): (21,0%)
  - EPS (Earnings Per Share): 2.500
  - BVPS (Book Value Per Share): 18.946
  - Nợ/VCSH (lần): 0,9
  - ROA (Return on Assets): 5,7%
  - ROE (Return on Equity): 14,2%

- **2025F:**
  - Doanh thu (Sales): 143,549
  - %YoY (Year-over-Year Growth): (10,3%)
  - LNG (Natural Gas): 31,850
  - Biên LNG (%): 21,7%
  - LNST Công ty mẹ (Natural Gas Sales): 4.427
  - %YoY (Year-over-Year Growth): (16,5%)
  - EPS (Earnings Per Share): 3.027
  - BVPS (Book Value Per Share): 21.973
  - Nợ/VCSH (lần): 0,9
  - ROA (Return on Assets): 6,5%
  - ROE (Return on Equity): 16,5%

### Analysis:
- **MWG (Mega World Group):**
  - Sales growth is moderate, with a year-over-year growth rate of 10.3%.
  - LNG sales are relatively high, contributing to the company's revenue.
  - EPS and BVPS are relatively low, indicating lower profitability.
  - ROA and ROE are also low, suggesting poor financial performance.

- **FRT (Forte Retail):**
  - Sales growth is moderate, with a year-over-year growth rate of 10.3%.
  - LNG sales are relatively high, contributing to the company's revenue.
  - EPS and BVPS are relatively low, indicating lower profitability.
  - ROA and ROE are also low, suggesting poor financial performance.

- **PNJ (Phúc Nông JSC):**
  - Sales growth is moderate, with a year-over-year growth rate of 10.3%.
  - LNG sales are relatively high, contributing to the company's revenue.
  - EPS and BVPS are relatively low, indicating lower profitability.
  - ROA and ROE are also low, suggesting poor financial performance.

### Conclusion:
The financial performance of all three companies is generally poor, with low sales growth, low profitability, and low earnings per share. The companies


[System] You are Project A, an expert Data Analyst.

[User] Thị trường bán lẻ Việt Nam có tốc độ tăng trưởng như thế nào so với các nước khác và tiềm năng trong tương lai?

[Assistant]
<think>I analyzed the provided OCR text from the visual data, which describes Vietnam's retail market. Key points extracted: Vietnam's retail market has a Compound Annual Growth Rate (CAGR) of 12.05% for 2023-2028, about twice the GDP growth rate. It is projected to enter the top 30 global consumer markets by the end of the decade, indicating rapid expansion compared to other countries like China, India, and those in Southeast Asia. The business insight is that Vietnam's retail sector is one of the fastest-growing globally, offering high potential for investment and business opportunities. For the scenario, I imagined a Vietnamese store owner asking about growth rates and market potential to make informed decisions. The response should cite specific data from the graph to provide a clear answer.</think>
Dựa vào biểu đồ từ báo cáo, thị trường bán lẻ Việt Nam có tốc độ tăng trưởng kép hàng năm (CAGR) đạt 12.05% trong giai đoạn 2023-2028, nhanh hơn khoảng gấp đôi tốc độ tăng trưởng GDP và thuộc nhóm dẫn đầu trong khu vực Đông Nam Á. Việt Nam được dự báo sẽ lọt vào top 30 thị trường tiêu dùng lớn nhất thế giới vào cuối thập kỷ này, cho thấy tiềm năng phát triển mạnh mẽ và cơ hội tốt cho các chủ cửa hàng trong nước.


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

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

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

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

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

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

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

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

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

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

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

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