Digital Labor Force Planning Driven Educational Project Management to Enhance Graduate Employability in Chinese Universities with a Case Study of Pingdingshan University

Abstract

Amid global industrial transformation and the expanding scale of Chinese college graduates, the mismatch between higher education outputs and labor market demands has become a pressing issue, leading to suboptimal graduate employment absorption. A critical gap lies in the lack of systematic integration of data-driven digital labor force planning (DLFP) into educational project management (EPM). This study aims to address this gap by constructing a feasible DLFP-driven EPM model to enhance graduate employability, with Pingdingshan University as a case study. Adopting an exploratory sequential mixed-methods design, the qualitative phase involves in-depth interviews, focus group discussions, and document analysis with 48 key stakeholders (program directors, faculty, students, alumni, and industry representatives) to identify critical influencing factors. The quantitative phase utilizes a structured questionnaire (targeting 260 respondents) and Partial Least Squares Structural Equation Modeling (PLS-SEM) to test relationships among five independent variables (demand forecasting, curriculum-job matching, competency mapping, work-integrated learning, career services), one mediating variable (employment readiness), and one dependent variable (graduate employability). Expected results include identifying bottlenecks in current EPM (e.g., inadequate digital demand forecasting, poor curriculum-job matching), validating the positive impact of DLFP on employability, and proposing a four-module EPM framework. Theoretically, this study enriches the literature on higher education governance and DLFP; practically, it provides actionable strategies for Chinese universities to bridge the industry-education gap and enhance graduate competitiveness, contributing to regional economic development and sustainable development goals (SDGs).