Environmental, Social and Governance Report 2024
Extracted ESG KPIs
KPIs are organized by ESG aspects.
The types of emissions and respective emissions data.
| Indicator | Unit | 2023 | 2024 | Report Pages |
|---|---|---|---|---|
| Nitrogen oxide (NOx) emissions | kg | 532.7 | 334.8 | 59 |
| Particular matter (PM) emissions | kg | 43.6 | 31.1 | 59 |
| Sulfur oxide (SOx) emissions | kg | 1.2 | 3.3 | 59 |
Direct (Scope 1) and energy indirect (Scope 2) greenhouse gas emissions (in tonnes) and, where appropriate, intensity (e.g. per unit of production volume, per facility).
| Indicator | Unit | 2023 | 2024 | Report Pages |
|---|---|---|---|---|
| Direct emissions (Scope 1) | tonnes of CO2e | 218.7 | 1252.8 | 59 |
| Equivalent to a reduction of about | tonnes of CO2 | 15749.2 | 9 | |
| Greenhouse gas emissions intensity | tonnes of CO2e/ten million RMB | 65.8 | 61.3 | 59 |
| Indirect emissions (Scope 2) | tonnes of CO2e | 73437.9 | 71083.1 | 59 |
| Total greenhouse gas (GHG) emissions | tonnes of CO2e | 72335.9 | 9 | |
| Total greenhouse gas emissions | tonnes of CO2e | 73656.6 | 72335.9 | 59 |
Total hazardous waste produced (in tonnes) and, where appropriate, intensity (e.g. per unit of production volume, per facility).
| Indicator | Unit | 2023 | 2024 | Report Pages |
|---|---|---|---|---|
| Hazardous waste intensity | tonnes/ten million RMB | 0.2 | 0.3 | 59 |
| Other industrial wastes | tonnes | 564.3 | 93.5 | 59 |
| Total hazardous waste | tonnes | 238.7 | 372.4 | 59 |
Total non-hazardous waste produced (in tonnes) and, where appropriate, intensity (e.g. per unit of production volume, per facility).
| Indicator | Unit | 2023 | 2024 | Report Pages |
|---|---|---|---|---|
| Domestic waste | tonnes | 1857 | 3523.2 | 59 |
| Metal non-hazardous waste | tonnes | 59.4 | 89.8 | 59 |
| Non-hazardous waste intensity | tonnes/ten million RMB | 2.7 | 3.5 | 59 |
| Paper non-hazardous waste | tonnes | 296 | 374.2 | 59 |
| Plastics non-hazardous waste | tonnes | 189.1 | 83.8 | 59 |
| Total non-hazardous waste | tonnes | 2965.7 | 4164.5 | 59 |
Description of emissions target(s) set and steps taken to achieve them.
| Indicator | Unit | 2024 | 2030 | 2050 | Report Pages |
|---|---|---|---|---|---|
| Sets of packaging equipment transformed in factories | sets | 14 | 42 | ||
| Targeted achievement of Scope I and Scope II Carbon Neutrality | Carbon Neutrality | 28 | |||
| Targeted reduction in Scope I and Scope II emissions using 2022 as the base year | reduction | 50% | 28 |
Direct and/or indirect energy consumption by type (e.g. electricity, gas or oil) in total (kWh in '000s) and intensity (e.g. per unit of production volume, per facility).
| Indicator | Unit | 2023 | 2024 | Report Pages |
|---|---|---|---|---|
| Comprehensive energy consumption | kWh in '000s | 133086.1 | 9 | |
| Diesel oil | kWh in '000s | 141.7 | 817.5 | 59 |
| Gasoline | kWh in '000s | 615.7 | 1768.2 | 59 |
| Green electricity purchases | kWh in '000s | 3500 | 29350 | 9, 59 |
| Natural gas | kWh in '000s | 2215.4 | 59 | |
| Purchased electricity | kWh in '000s | 126171.5 | 128285 | 59 |
| Total energy consumption | kWh in '000s | 126944.7 | 133086.1 | 59 |
| Total energy consumption intensity | kWh in '000s/ten million RMB | 113.7 | 112.8 | 59 |
Water consumption in total and intensity (e.g. per unit of production volume, per facility).
| Indicator | Unit | 2023 | 2024 | Report Pages |
|---|---|---|---|---|
| Decrease in water consumption from 2023 | 6.6% | 28 | ||
| Freshwater consumption | tonnes | 826349.2 | 771639.7 | 59 |
| Freshwater consumption intensity | tonnes/ten million RMB | 739.9 | 654 | 59 |
| Freshwater withdrawal | tonnes | 826349.2 | 771639.7 | 59 |
| Freshwater withdrawal intensity | tonnes/ten million RMB | 739.9 | 654 | 59 |
| Total water consumption | metric tons, tonnes | 826349.2 | 771639.7 | 28, 59 |
| Total water discharge | tonnes | 826349.2 | 771639.7 | 59 |
| Total water withdrawal | tonnes | 826349.2 | 771639.7 | 59 |
Description of energy use efficiency target(s) set and steps taken to achieve them.
| Indicator | Unit | 2023 | 2024 | Report Pages |
|---|---|---|---|---|
| Cost reduction from nine distributions of improvement practices | million RMB | 1 | 42 | |
| Expected green electricity reduction | tonnes of CO2e | 1332.8 | 15749.2 | 59 |
| Investment amount saved by transformation of packaging equipment | million RMB | 2 | 42 |
Total packaging material used for finished products (in tonnes) and, if applicable, with reference to per unit produced.
| Indicator | Unit | 2023 | 2024 | Report Pages |
|---|---|---|---|---|
| Metal packaging consumption | tonnes | 192.5 | 189 | 59 |
| Packaging consumption intensity | tonnes/ten million RMB | 14.7 | 17.9 | 59 |
| Paper packaging consumption | tonnes | 14270.8 | 18977 | 59 |
| Plastics packaging consumption | tonnes | 1980.1 | 1961 | 59 |
| Total packaging consumption | tonnes | 16443.4 | 21127 | 59 |
Description of the significant impacts of activities on the environment and natural resources and the actions taken to manage them.
| Indicator | Unit | 2024 | February 2025 | Report Pages |
|---|---|---|---|---|
| MSCI ESG Rating | BBB | 7 | ||
| Number of indicators introduced in production operation data analysis platform | indicators | 48 | 42 | |
| Number of signage board interfaces introduced in production operation data analysis platform | interfaces | 13 | 42 | |
| Sustainalytics ESG risk score | 26.4 | 7 |
Description of the significant climate-related issues which have impacted, and those which may impact, the issuer, and the actions taken to manage them.
| Indicator | Unit | 2024 | 2030 | 2050 | Report Pages |
|---|---|---|---|---|---|
| Expected financial loss risk level for coastal flooding under SSP1-2.6 scenario in 2024 | Low risk | 24 | |||
| Expected financial loss risk level for coastal flooding under SSP1-2.6 scenario in 2030 | Low risk | 24 | |||
| Expected financial loss risk level for coastal flooding under SSP1-2.6 scenario in 2050 | Medium risk | 24 | |||
| Expected financial loss risk level for coastal flooding under SSP5-8.5 scenario in 2024 | Medium risk | 24 | |||
| Expected financial loss risk level for coastal flooding under SSP5-8.5 scenario in 2030 | Medium risk | 24 | |||
| Expected financial loss risk level for coastal flooding under SSP5-8.5 scenario in 2050 | High risk | 24 | |||
| Expected financial loss risk level for extreme heat under SSP1-2.6 scenario in 2024 | Low risk | 24 | |||
| Expected financial loss risk level for extreme heat under SSP1-2.6 scenario in 2030 | Low risk | 24 | |||
| Expected financial loss risk level for extreme heat under SSP1-2.6 scenario in 2050 | Medium risk | 24 | |||
| Expected financial loss risk level for extreme heat under SSP5-8.5 scenario in 2024 | Medium risk | 24 | |||
| Expected financial loss risk level for extreme heat under SSP5-8.5 scenario in 2030 | Medium risk | 24 | |||
| Expected financial loss risk level for extreme heat under SSP5-8.5 scenario in 2050 | High risk | 24 | |||
| Expected financial loss risk level for extreme rainfall under SSP1-2.6 scenario in 2024 | Low risk | 24 | |||
| Expected financial loss risk level for extreme rainfall under SSP1-2.6 scenario in 2030 | Low risk | 24 | |||
| Expected financial loss risk level for extreme rainfall under SSP1-2.6 scenario in 2050 | Medium risk | 24 | |||
| Expected financial loss risk level for extreme rainfall under SSP5-8.5 scenario in 2024 | Medium risk | 24 | |||
| Expected financial loss risk level for extreme rainfall under SSP5-8.5 scenario in 2030 | Medium risk | 24 | |||
| Expected financial loss risk level for extreme rainfall under SSP5-8.5 scenario in 2050 | High risk | 24 | |||
| Expected financial loss risk level for typhoon under SSP1-2.6 scenario in 2024 | Low risk | 24 | |||
| Expected financial loss risk level for typhoon under SSP1-2.6 scenario in 2030 | Low risk | 24 | |||
| Expected financial loss risk level for typhoon under SSP1-2.6 scenario in 2050 | Medium risk | 24 | |||
| Expected financial loss risk level for typhoon under SSP5-8.5 scenario in 2024 | Medium risk | 24 | |||
| Expected financial loss risk level for typhoon under SSP5-8.5 scenario in 2030 | Medium risk | 24 | |||
| Expected financial loss risk level for typhoon under SSP5-8.5 scenario in 2050 | High risk | 24 |
Total workforce by gender, employment type (for example, full- or part-time), age group and geographical region.
| Indicator | Unit | 2023 | 2024 | Report Pages |
|---|---|---|---|---|
| Engagement rate of authorized users within the Group in production operation data analysis platform | % | 42.7 | 42 | |
| Number of R&D personnel | Headcounts | 1480 | 1609 | 61 |
| Number of employees aged 21-40 years | persons | 13743 | 51 | |
| Number of employees aged 41-50 years | persons | 2417 | 51 | |
| Number of employees by age: 21-40 years old | Headcounts | 10794 | 13743 | 60 |
| Number of employees by age: 41-50 years old | Headcounts | 1832 | 2263 | 60 |
| Number of employees by age: Above 50 years old | Headcounts | 138 | 143 | 60 |
| Number of employees by age: Below 20 years old | Headcounts | 542 | 2417 | 60 |
| Number of employees by employment type: Full-time | Headcounts | 13306 | 18566 | 60 |
| Number of employees by gender: Female | Headcounts | 7135 | 8938 | 60 |
| Number of employees by gender: Male | Headcounts | 6171 | 9628 | 60 |
| Number of employees by region: Mainland China | Headcounts | 11556 | 16560 | 60 |
| Number of employees by region: Overseas (including Hong Kong, Macau, and Taiwan) | Headcounts | 1750 | 2006 | 60 |
| Number of employees in Mainland China | persons | 16560 | 51 | |
| Number of employees in Overseas (including Hong Kong, Macao and Taiwan) | persons | 2006 | 51 | |
| Number of employees over 50 years old | persons | 143 | 51 | |
| Number of employees under 20 years | persons | 2263 | 51 | |
| Number of female employees | persons | 9628 | 51 | |
| Number of full-time employees | persons | 18566 | 51 | |
| Number of general and technical employees | persons | 16975 | 51 | |
| Number of male employees | persons | 8938 | 51 | |
| Number of middle and senior management employees | persons | 1591 | 51 | |
| Number of middle management employees | persons | 1239 | 51 | |
| Number of senior management employees | persons | 352 | 51 | |
| Percentage of men in middle and senior management | 76% | 51 | ||
| Percentage of women in middle and senior management | 24% | 51 | ||
| Total assets | RMB '000 | 27654378 | 9 | |
| Total number of employees | Headcounts, employees, persons | 13306 | 18566 | 9, 51, 60 |
Employee turnover rate by gender, age group and geographical region.
| Indicator | Unit | 2023 | 2024 | Report Pages |
|---|---|---|---|---|
| Employee average turnover by age: 21-40 years old | % | 7.3 | 5.8 | 60 |
| Employee average turnover by age: 41-50 years old | % | 4.6 | 4.6 | 60 |
| Employee average turnover by age: Above 50 years old | % | 3.7 | 3.3 | 60 |
| Employee average turnover by age: Below 20 years old | % | 9.5 | 6.9 | 60 |
| Employee average turnover by gender: Female | % | 6.8 | 5.5 | 60 |
| Employee average turnover by gender: Male | % | 7.3 | 6.3 | 60 |
| Employee average turnover by region: Hong Kong | % | 0.5 | 60 | |
| Employee average turnover by region: Mainland China | % | 7.7 | 6.1 | 60 |
| Employee average turnover by region: Overseas | % | 1.1 | 1.6 | 60 |
Lost days due to work injury.
| Indicator | Unit | 2023 | 2024 | Report Pages |
|---|---|---|---|---|
| Number of lost days due to work-related injuries | Days | 146 | 370.5 | 61 |
The percentage of employees trained by gender and employee category (e.g. senior management, middle management).
| Indicator | Unit | 2023 | 2024 | Report Pages |
|---|---|---|---|---|
| Bachelors and Masters Intensive new employee orientation courses | courses | 27 | 54 | |
| Bachelors and Masters Intensive new employee orientation overall satisfaction rating | points | 98 | 54 | |
| Bachelors and Masters Intensive new employee orientation participants | participants | 44 | 54 | |
| Bachelors and Masters Intensive new employee orientation sessions | sessions | 7 | 54 | |
| Hongyi Program (director-level training) participants | participants | 21 | 54 | |
| Key Talent Intensive Training overall satisfaction rating | points | 93.3 | 54 | |
| Key Talent Intensive Training participants | participants | 35 | 54 | |
| Key Talent Intensive Training sessions | sessions | 2 | 54 | |
| Percentage of all employees trained | 100% | 54 | ||
| Percentage of female employees trained | 100% | 54 | ||
| Percentage of general and technical employees trained | 100% | 54 | ||
| Percentage of male employees trained | 100% | 54 | ||
| Percentage of middle managers trained | 100% | 54 | ||
| Percentage of senior managers trained | 100% | 54 | ||
| Percentage of trained employees | % | 100 | 100 | 60 |
| Pre-departure training for sea-going personnel participants | participants | 96 | 54 | |
| Proportion of employees trained | % | 100 | 9 | |
| R&D expenditure | thousand RMB | 1482846 | 1572313 | 61 |
| R&D investment | RMB | 1572313000 | 9 | |
| R&D project empowerment intensive training participants | participants | 68 | 54 | |
| Regular newcomer training overall satisfaction rating | points | 98 | 54 | |
| Regular newcomer training participants | participants | 463 | 54 | |
| Regular newcomer training sessions | sessions | 12 | 54 | |
| TPM special improvement week participants | participants | 50 | 54 | |
| Total number of employees trained | employees | 18566 | 54 | |
| Zhenyu Program (manager-level training) business division participants | participants | 198 | 54 | |
| Zhenyu Program (manager-level training) business division phases | phases | 2 | 54 | |
| Zhenyu Program (manager-level training) phases | phases | 3 | 54 |
The average training hours completed per employee by gender and employee category.
| Indicator | Unit | 2023 | 2024 | Report Pages |
|---|---|---|---|---|
| Average training hours per person | Hours | 37.1 | 39.9 | 60 |
| Average training hours per person by gender: Female | Hours | 33.2 | 38.1 | 60 |
| Average training hours per person by gender: Male | Hours | 41.8 | 41.6 | 60 |
| Average training hours per person by job level: General and technical personnel | Hours | 37.7 | 40.4 | 60 |
| Average training hours per person by job level: Middle management | Hours | 32.9 | 35.9 | 60 |
| Average training hours per person by job level: Senior management | Hours | 30.3 | 30.2 | 60 |
| Average training time for all employees | hours | 39.9 | 54 | |
| Average training time for female employees | hours | 38.1 | 54 | |
| Average training time for general and technical employees | hours | 40.4 | 54 | |
| Average training time for male employees | hours | 41.6 | 54 | |
| Average training time for middle managers | hours | 35.9 | 54 | |
| Average training time for senior managers | hours | 30.2 | 54 | |
| Total employee training hours | Hours | 494311 | 740969 | 60 |
| Training and development expenditures | RMB | 2879000 | 54 |
Number of suppliers by geographical region.
| Indicator | Unit | 2023 | 2024 | Report Pages |
|---|---|---|---|---|
| Total number of suppliers | Number of suppliers | 453 | 541 | 61 |
| Total number of suppliers - Mainland China | Number of suppliers | 418 | 473 | 61 |
| Total number of suppliers - Overseas (including Hong Kong, Macau, and Taiwan) | Number of suppliers | 35 | 68 | 61 |
Description of practices relating to engaging suppliers, number of suppliers where the practices are being implemented, and how they are implemented and monitored.
| Indicator | Unit | 2023 | 2024 | Report Pages |
|---|---|---|---|---|
| Ratio of suppliers signing integrity commitment | % | 83 | 100 | 61 |
Number of products and service related complaints received and how they are dealt with.
| Indicator | Unit | 2024 | Report Pages |
|---|---|---|---|
| Product design ability enhancement special empowerment participants | participants | 48 | 54 |
Description of practices relating to observing and protecting intellectual property rights.
| Indicator | Unit | 2023 | 2024 | Report Pages |
|---|---|---|---|---|
| New invention patents filed | quantity | 1172 | 893 | 61 |
| New patents applications filed | quantity | 2033 | 1558 | 61 |
| New patents authorized | quantity | 988 | 825 | 61 |
| Patents applications filed - Design patents | quantity | 1896 | 2259 | 61 |
| Patents applications filed - Invention patents | quantity | 3867 | 4760 | 61 |
| Patents applications filed - Total | quantity | 7695 | 9253 | 61 |
| Patents applications filed - Utility model patents | quantity | 1932 | 2234 | 61 |
| Registered valid patents - Design patents | quantity | 1371 | 1603 | 61 |
| Registered valid patents - Invention patents | quantity | 490 | 842 | 61 |
| Registered valid patents - Total | quantity | 3389 | 4214 | 61 |
| Registered valid patents - Utility model patents | quantity | 1528 | 1769 | 61 |
Number of concluded legal cases regarding corrupt practices brought against the issuer or its employees during the reporting period and the outcomes of the cases.
| Indicator | Unit | 2023 | 2024 | September 2024 | Report Pages |
|---|---|---|---|---|---|
| Number of concluded corruption litigation cases filed against the enterprise or its employees | Cases | 2 | 2 | 61 | |
| S&P Global ESG Rating score | points | 38 | 7 |
Description of anti-corruption training provided to directors and staff.
| Indicator | Unit | 2023 | 2024 | Report Pages |
|---|---|---|---|---|
| Times of anti-corruption training | Times | 14 | 14 | 61 |
| Total anti-corruption training hours | Hours | 600 | 499 | 61 |
Focus areas of contribution (e.g. education, environmental concerns, labour needs, health, culture, sport).
| Indicator | Unit | 2023 | 2024 | Q1 2025 | Report Pages |
|---|---|---|---|---|---|
| China Securities Index (CSI) ESG Rating | A | 7 | |||
| Number people engaged in public welfare/volunteering activities | Headcounts | 38 | 25 | 61 |
Resources contributed (e.g. money or time) to the focus area.
| Indicator | Unit | 2023 | 2024 | Report Pages |
|---|---|---|---|---|
| Amount invested in public welfare initiatives | RMB | 6332990 | 4 | |
| Grand Lecture sharing session participants | people | 1000 | 54 | |
| Grand Lecture sharing sessions | sessions | 7 | 54 | |
| Hours participated in community service | hours | 255 | 4 | |
| Individuals involved in social welfare activities | individuals | 25 | 4 | |
| Investment in public welfare activities | RMB | 6332990 | 9 | |
| Public welfare expenditure | RMB | 8274461 | 6332990 | 61 |
| Public welfare/volunteering activities hours | Hours | 207 | 255 | 61 |
| Total equity | RMB '000 | 21904711 | 9 |
The types of emissions and respective emissions data.
| Standard Indicator | Unit | 2023 | 2024 |
|---|---|---|---|
| Airborne Particulate Matter (PM) Emissions | kg | 43.6 | 31.1 |
| NOâ‚“ Emissions | kg | 532.7 | 334.8 |
| SOâ‚“ Emissions | kg | 1.2 | 3.3 |
Direct (Scope 1) and energy indirect (Scope 2) greenhouse gas emissions (in tonnes) and, where appropriate, intensity (e.g. per unit of production volume, per facility).
| Standard Indicator | Unit | 2023 | 2024 |
|---|---|---|---|
| Direct GHG Emissions (Scope 1) | tonnes of CO2e | 218.7 | 1252.8 |
| Indirect Energy Emissions (Scope 2) | tonnes of CO2e | 73437.9 | 71083.1 |
| Total GHG Emissions | tonnes of CO2e | 73656.6 | 72335.9 |
| Total GHG Emissions Intensity (By Revenue) | tonnes of CO2e/ten million RMB | 65.8 | 61.3 |
Total hazardous waste produced (in tonnes) and, where appropriate, intensity (e.g. per unit of production volume, per facility).
| Standard Indicator | Unit | 2023 | 2024 |
|---|---|---|---|
| Total Hazardous Waste | tonnes | 238.7 | 372.4 |
| Total Hazardous Waste Intensity (By Revenue) | tonnes/ten million RMB | 0.2 | 0.3 |
Total non-hazardous waste produced (in tonnes) and, where appropriate, intensity (e.g. per unit of production volume, per facility).
| Standard Indicator | Unit | 2023 | 2024 |
|---|---|---|---|
| Non-Hazardous Waste (Domestic Waste) | tonnes | 1857 | 3523.2 |
| Paper Waste | tonnes | 296 | 374.2 |
| Plastic Waste | tonnes | 189.1 | 83.8 |
| Total Non-Hazardous Waste Intensity (By Revenue) | tonnes/ten million RMB | 2.7 | 3.5 |
Description of emissions target(s) set and steps taken to achieve them.
| Standard Indicator | Unit | 2030 |
|---|---|---|
| Scope 1 and 2 Emissions Reduction Percentage Compared to Last Year | % | 50 |
Direct and/or indirect energy consumption by type (e.g. electricity, gas or oil) in total (kWh in '000s) and intensity (e.g. per unit of production volume, per facility).
| Standard Indicator | Unit | 2023 | 2024 |
|---|---|---|---|
| Diesel Fuel Consumption | kWh in '000s | 141.7 | 817.5 |
| Energy Consumption Intensity (By Revenue) | kWh in '000s/ten million RMB | 113.7 | 112.8 |
| Gasoline Consumption | kWh in '000s | 615.7 | 1768.2 |
| Natural Gas Consumption | kWh in '000s | 2215.4 | |
| Purchased Electricity | kWh in '000s | 126171.5 | 128285 |
| Renewable Energy Consumption | kWh in '000s | 3500 | 29350 |
| Total Energy Consumption | kWh in '000s | 126944.7 | 133086.1 |
Water consumption in total and intensity (e.g. per unit of production volume, per facility).
| Standard Indicator | Unit | 2023 | 2024 |
|---|---|---|---|
| Total Wastewater Discharge | tonnes | 826349.2 | 771639.7 |
| Total Water Withdrawal | tonnes | 826349.2 | 771639.7 |
| Water Consumption | tonnes | 826349.2 | 771639.7 |
| Water Consumption Intensity (By Revenue) | tonnes/ten million RMB | 739.9 | 654 |
| Water Withdrawal Intensity | tonnes/ten million RMB | 739.9 | 654 |
Description of energy use efficiency target(s) set and steps taken to achieve them.
| Standard Indicator | Unit | 2023 |
|---|---|---|
| Energy Consumption Reduction Percentage Compared to Last Year | % | -1 |
Total packaging material used for finished products (in tonnes) and, if applicable, with reference to per unit produced.
| Standard Indicator | Unit | 2023 | 2024 |
|---|---|---|---|
| Packaging Material Consumption (Metal) | tonnes | 192.5 | 189 |
| Packaging Material Consumption (Plastic) | tonnes | 1980.1 | 1961 |
| Packaging Material Intensity (By Revenue) | tonnes/ten million RMB | 14.7 | 17.9 |
| Packaging Materials Consumed | tonnes | 16443.4 | 21127 |
Total workforce by gender, employment type (for example, full- or part-time), age group and geographical region.
| Standard Indicator | Unit | 2023 | 2024 |
|---|---|---|---|
| Number of Employees Aged 30-50 | Headcounts | 12626 | 15980 |
| Number of Employees Aged Above 50 | Headcounts | 138 | 143 |
| Number of Employees Aged Below 30 | Headcounts | 542 | 2263 |
| Number of Employees in Mainland China | Headcounts | 11556 | 16560 |
| Number of Employees in Overseas | Headcounts | 1750 | 2006 |
| Number of Female Employees | Headcounts | 7135 | 9628 |
| Number of Full-time Employees | Headcounts | 13306 | 18566 |
| Number of Male Employees | Headcounts | 6171 | 8938 |
| Number of Middle Management Employees | persons | 1239 | |
| Number of Senior Management Employees | persons | 352 | |
| Number of Total Employees | Headcounts | 13306 | 18566 |
| Percentage of Employees Aged 30-50 | % | 94.92 | 86.13 |
| Percentage of Employees Aged Above 50 | % | 1.04 | 0.77 |
| Percentage of Employees Aged Below 30 | % | 4.08 | 12.19 |
| Percentage of Employees in Mainland China | % | 86.89 | 89.25 |
| Percentage of Employees in Overseas | % | 13.15 | 10.81 |
| Percentage of Female Employees | % | 53.6 | 51.84 |
| Percentage of Full-time Employees | % | 100 | 100 |
| Percentage of Male Employees | % | 46.4 | 48.16 |
Employee turnover rate by gender, age group and geographical region.
| Standard Indicator | Unit | 2023 | 2024 |
|---|---|---|---|
| Turnover Rate of Employees in Hong Kong | % | 0.5 | |
| Turnover Rate of Employees in Mainland China | % | 7.7 | 6.1 |
| Turnover Rate of Employees in Overseas | % | 1.1 | 1.6 |
| Turnover Rate of Female Employees | % | 6.8 | 5.5 |
| Turnover Rate of Male Employees | % | 7.3 | 6.3 |
Lost days due to work injury.
| Standard Indicator | Unit | 2023 | 2024 |
|---|---|---|---|
| Lost Days Due to Work-related Injuries | Days | 146 | 370.5 |
The percentage of employees trained by gender and employee category (e.g. senior management, middle management).
| Standard Indicator | Unit | 2023 | 2024 |
|---|---|---|---|
| Percentage of Employees Trained | % | 100 | 100 |
| Percentage of Trained Female Employees | % | 100 | |
| Percentage of Trained General Employees | % | 100 | |
| Percentage of Trained Male Employees | % | 100 | |
| Percentage of Trained Middle Management | % | 100 | |
| Percentage of Trained Senior Management | % | 100 | |
| Percentage of Trained Technical Employees | % | 100 |
The average training hours completed per employee by gender and employee category.
| Standard Indicator | Unit | 2023 | 2024 |
|---|---|---|---|
| Average Training Hours (Female) | Hours | 33.2 | 38.1 |
| Average Training Hours (General Staff) | Hours | 37.7 | 40.4 |
| Average Training Hours (Male) | Hours | 41.8 | 41.6 |
| Average Training Hours (Middle Management) | Hours | 32.9 | 35.9 |
| Average Training Hours (Senior Management) | Hours | 30.3 | 30.2 |
| Average Training Hours per Employee | Hours | 37.1 | 39.9 |
| Total Training Hours | Hours | 494311 | 740969 |
Number of suppliers by geographical region.
| Standard Indicator | Unit | 2023 | 2024 |
|---|---|---|---|
| Number of Suppliers in Mainland China | Number of suppliers | 418 | 473 |
| Number of Total Suppliers | Number of suppliers | 453 | 541 |
Description of practices relating to observing and protecting intellectual property rights.
| Standard Indicator | Unit | 2023 | 2024 |
|---|---|---|---|
| Accumulative Number of Patent Applications | quantity | 7695 | 9253 |
| Accumulative Number of Patents Granted | quantity | 988 | 825 |
| Number of Authorised Utility Model Patents | quantity | 1528 | 1769 |
| Number of Invention Patents | quantity | 490 | 842 |
| Number of New Patent Applications | quantity | 2033 | 1558 |
| Number of Patents Applied | quantity | 7695 | 9253 |
| Number of Patents Granted | quantity | 988 | 825 |
| Number of Patents Held | quantity | 3389 | 4214 |
Number of concluded legal cases regarding corrupt practices brought against the issuer or its employees during the reporting period and the outcomes of the cases.
| Standard Indicator | Unit | 2023 | 2024 |
|---|---|---|---|
| Number of Concluded Corruption Lawsuits | Cases | 2 | 2 |
Description of anti-corruption training provided to directors and staff.
| Standard Indicator | Unit | 2023 | 2024 |
|---|---|---|---|
| Number of Anti-corruption Training Session | Times | 14 | 14 |
| Total Hours of Anti-corruption Training | Hours | 600 | 499 |
Resources contributed (e.g. money or time) to the focus area.
| Standard Indicator | Unit | 2023 | 2024 |
|---|---|---|---|
| Total Public Welfare Donations | RMB | 8274461 | 6332990 |
| Total Social Investment | RMB | 8274461 | 6332990 |
| Total Volunteer Service Hours | hours | 207 | 255 |