CnOpenData systematically extracts recruitment information primarily from accounting firms across multiple mainstream online recruitment platforms (Sources B/C/E) to construct the Online Recruitment Database for Accounting Firms. This dataset comprehensively integrates information about recruiting entities, position details, qualification requirements, and compensation benefits, transforming fragmented online recruitment data into standardized structured information. Core fields encompass critical information such as company name, location, position title, number of vacancies, compensation, language requirements, work experience, education background, and posting date. It provides an irreplaceable micro-level foundation for observing the talent demand structure of accounting firms, regional talent mobility trends, and dynamics in the human resources market of the industry. This serves as a key resource for research in labor economics, human resource management, education policy, and industry development.
Key Features:
- Multi-dimensional Recruitment Demand Profile: The database includes not only basic company and position information but also detailed fields such as "Compensation," "Language Requirements," "Work Experience," "Education Background," and "Major Requirements." These are crucial for analyzing industry entry barriers, salary levels, skill preferences, and the evolution of talent structures, enabling a comprehensive characterization of the human resource demands of accounting firms.
- Support for Spatio-temporal Dynamic Analysis: Covering major cities nationwide with a long time span (2014 to 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 practices of accounting firms.
- Precise Industry Focus: The data strictly limits recruiting entities to accounting firms and their branches, ensuring industry purity of research samples. This effectively addresses the challenge of filtering industry-specific data from comprehensive recruitment platforms, providing a reliable foundation for precise industry-level research.
Application Value:
- Academic Research: Supports research in labor economics (labor market segmentation, skill premiums), human resource management (recruitment strategies, competency models), education policy (alignment between academic programs and market demand), and industrial organization (expansion and competition among accounting firms), offering micro-empirical evidence for related theories.
- Industry Insights and Career Planning: Assists university students, job seekers, and career development institutions in understanding real-time talent demands, salary ranges, and competency requirements of accounting firms, providing data-driven decision support for personal career planning, major selection, and skill enhancement.
- Business and Policy Decision-making: Provides market references for accounting firms to formulate or adjust recruitment strategies and regional human resource allocation. Simultaneously, it offers data support for education departments and industry associations to evaluate talent cultivation quality and predict industry talent supply-demand gaps.
With its precise focus on accounting firms as recruiting entities and deep extraction of multi-dimensional recruitment demand information, this dataset establishes a critical data nexus connecting micro-level corporate talent needs with the macro-level human resources market. It serves as essential infrastructure for observing development trends in the accounting industry, analyzing professional talent mobility patterns, and evaluating the effectiveness of higher education programs in related fields, providing robust data support for academic research, individual development, and industry decision-making.
Articles Citing This Dataset
Data Scale
Time Period
2014.05-2024
Field Display
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
- Jingyu Gao & Rui Wei, 2024: "Digital Transformation of Accounting Firms and Audit Quality: Empirical Evidence from Digital Talent Recruitment," Auditing Research, No. 3.
Data Update Frequency
Annual updates