CnOpenData systematically extracts recruitment information targeting accounting firms from multiple mainstream online recruitment platforms (Platforms B, C, and E) to construct the Online Recruitment Database for Accounting Firms. This dataset deeply integrates employer information, position details, qualification requirements, and compensation benefits, transforming scattered online recruitment data into standardized structured data. Core fields encompass critical information such as company name, location, position title, number of hires, compensation package, language requirements, years of work experience, education level, and posting date. This provides an indispensable micro-level foundation for observing the talent demand structure of accounting firms, regional talent mobility trends, and labor market dynamics within the industry. It serves as a key resource for research in labor economics, human resource management, education policy, and industry development.
Data Features:
- Multi-dimensional Recruitment Demand Profiling: Beyond basic company and position information, the database comprehensively includes in-depth fields such as "Compensation," "Language Requirements," "Years of Work Experience," "Education Level," and "Major Requirements." These serve as critical evidence for analyzing industry entry barriers, salary levels, skill preferences, and the evolution of talent structure, enabling a holistic depiction of the human resource demand characteristics within accounting firms.
- Support for Spatio-temporal Dynamic Analysis: Covering major cities nationwide and spanning an extended timeframe (2014 to the present), the data enables researchers to conduct cross-regional comparisons of talent demand, analyze long-term talent demand trends, and assess the impact of specific economic policies or industry events on the recruitment behaviors of accounting firms.
- Precise Industry Focus: The data strictly limits recruitment entities to accounting firms and their branches, ensuring industry purity in the research sample. This effectively addresses the challenge of filtering industry-specific data from comprehensive recruitment platforms, providing a reliable foundation for precise industry-level research.
Data Application Value:
- Academic Research: Supports research in labor economics (e.g., labor market segmentation, skill premiums), human resource management (e.g., recruitment strategies, competency models), education policy (e.g., alignment of academic programs with market demands), and industrial organization (e.g., expansion and competition among accounting firms), providing micro-empirical evidence for relevant theories.
- Industry Insights and Career Planning: Assists university students, job seekers, and career development institutions in understanding the real-time talent demands, salary ranges, and competency requirements of accounting firms. Provides data-driven decision support for personal career planning, academic major selection, and skill enhancement.
- Business and Policy Decision-Making: Offers market references for accounting firms to formulate or adjust recruitment strategies and optimize regional human resource allocation. Simultaneously, provides data support for educational departments and industry associations to evaluate talent cultivation quality and forecast industry talent supply-demand gaps.
By precisely focusing on accounting firms as recruitment entities and deeply extracting multi-dimensional information on recruitment demands, this dataset constructs a crucial data bridge connecting micro-level corporate hiring needs with the macro-level human resource market. It serves as vital infrastructure for discerning development trends in the accounting industry, analyzing the mobility patterns of professionals, and evaluating the effectiveness of higher education programs in relevant fields. It provides robust data support for academic research, personal development, and industry decision-making.
Articles Citing This Dataset
Data Scale
Time Period
2014.05 - 2025
Field Display
| 会计师事务所线上招聘数据-B来源 | 会计师事务所线上招聘数据-C来源 | 会计师事务所线上招聘数据-E来源 |
| ---- | ---- | ---- |
| 公司名称 | 公司名称 | 公司名称 |
| 关联公司名称 | 关联公司名称 | 关联公司名称 |
| 公司地址 | 工作地点 | 工作地点所在区域 |
| 工作地点区域代码 | 工作地点所在区域 | 所在区域 |
| 所在区域 | 所在区域 | 所在城市 |
| 所在城市 | 所在城市 | 所在省份 |
| 所在省份 | 所在省份 | 岗位 |
| 岗位 | 岗位 | 职位描述 |
| 岗位描述 | 职位描述 | 职位类别 |
| 岗位标签 | 所属部门 | 待遇 |
| 岗位职能 | 待遇 | 招聘人数 |
| 所属部门 | 福利 | 工作经验 |
| 相关福利 | 下属人数 | 学历要求 |
| 招聘人数 | 汇报对象 | 工作性质 |
| 待遇 | 工作年限 | 发布日期 |
| 语言要求 | 年龄要求 | |
| 工作年限 | 语言要求 | |
| 学历 | 职位类型 | |
| 发布时间 | 学历要求 | |
| | 专业要求 | |
| | 性别要求 | |
| | 发布日期 | |
***
Sample Data
会计师事务所线上招聘数据-B来源
会计师事务所线上招聘数据-C来源
会计师事务所线上招聘数据-E来源
References
- Gao Jingyu, Wei Rui., 2024: "Digital Transformation of Accounting Firms and Audit Quality: Empirical Evidence from Digital Talent Recruitment," Auditing Research, Vol. 3.
Data Update Frequency
Annual Updates