A Cross-Level Analytical Framework of Talent Attraction: Integrating Organizational Characteristics, Employee Attitudes, and Justice Perceptions
Abstract
In the digital economy era, attracting and retaining talent has become a critical ch In the digital economy era, attracting and retaining talent has become a critical challenge for organizations. Previous research has often examined organizational innovation climate, organizational support, and employee attitudes in isolation, lacking an integrated perspective that explains how these elements jointly shape talent attraction across organizational levels. Drawing on related theories, this paper proposes a cross-level conceptual model linking organizational characteristics—specifically innovation climate and perceived organizational support—to employee attitudes, including job satisfaction and organizational identification, to explain talent attraction. Organizational justice is introduced as a moderating condition influencing the strength of relationships between organizational characteristics and employee attitudes. The model also theorizes feedback effects from talent attraction to organizational dynamics, highlighting the cyclical nature of organizational development. This framework contributes to the literature by integrating organizational and individual perspectives into a coherent theoretical model that clarifies the mechanisms and contextual contingencies underlying talent attraction. It further offers practical implications for organizations aiming to enhance their attractiveness by cultivating supportive and innovative environments that strengthen employee satisfaction and identification. Directions for future empirical research are also outlined to validate and extend the proposed framework.
Fields of Study & Subjects
Employer Branding and e-HRM
Human Resource and Talent Management
Job Satisfaction and Organizational Behavior
Publication details
- Journal / source
- International Journal of Academic Research in Business and Social Sciences
- Volume
- 16
- Issue
- 1
- Publication date
- 18 January 2026
- Language
- EN