A Data-Driven Analysis of Career Development Trends on Professional Platforms through SEM using SmartPLS

This study evaluates the adoption of technology in digital recruitment platforms, such as LinkedIn, and its impact on improving career opportunities using an extended Theory of Planned Behavior (TPB) approach. Tests were conducted using the Partial Least Squares-Structural Equation Modelling (PLS-SEM) method to analyze the relationship between Perceived Usefulness (PU), Perceived Ease of Use (PEU), Attitude (ATT), Subjective Norms (SN), Price Value (PV), and Perceived Behavioral Control (PBC) on individuals' Intention (INT) to use LinkedIn. The results indicated that PU, PEU, ATT, and SN significantly influenced Intention, whereas PV and PBC showed no considerable effect. The findings suggest that perceived benefits, ease of use, positive attitudes, and social norms are significant factors in the adoption of digital recruitment platforms. In contrast, cost and perceived control are not significant determinants. This research contributes to understanding the factors that influence technology adoption on the digital recruitment platform LinkedIn and provides recommendations for platform developers and professionals in maximizing the use of technology for career development.