In the current era of Industry 4.0 and global digital transformation, the alignment between higher education and the labor market has become a pivotal driver for national innovation. As the provider of the world’s largest engineering education system, China presents a unique landscape where remarkable quantitative growth in STEM graduates is juxtaposed with a persistent and paradoxical skills gap. This research interrogates the Engineering Education-to-Workforce transition by analyzing the longitudinal trajectory of skill mismatch among engineering graduates from 2019 to 2023, a critical period marked by significant economic restructuring. The primary objective is to disentangle the mechanisms through which this mismatch suppresses initial wages while simultaneously reshaping the psychological well-being of early-career engineers.

To examine these complex consequences, the study constructs an interdisciplinary framework that initiates a dialogue between economic and psychological paradigms. We utilize Human Capital Theory (HCT) to quantify the economic wage penalty, positing that underutilized competencies inevitably diminish marginal productivity. However, we argue that the relationship between mismatch and job satisfaction is not a linear decline. While Person-Job Fit theory predicts reduced satisfaction due to environmental misalignment, we introduce Self-Determination Theory (SDT) as a potential moderating force. This study tests the hypothesis that if workplace environments fulfill basic psychological needs—specifically autonomy, competence, and relatedness—the activation of intrinsic motivation may buffer the negative impacts of mismatch, potentially explaining high professional well-being in mismatched roles.

The findings will offer critical insights that extend far beyond the Chinese context, positioning the country’s experience as a pivotal case study for the global academic community. China’s strategic shift from quantitative expansion to qualitative excellence provides a practical roadmap for other Global South nations navigating similar industrial pressures. By utilizing the O*NET database, this research ensures that "skills" are defined through a standardized global lens, facilitating direct benchmarking against the European Skills Agenda and North American STEM workforce standards. Ultimately, this study identifies universal patterns of decoupling between educational supply and industrial demand, offering evidence-based insights for international engineering education reform.

This study employs a quantitative research design utilizing repeated cross-sectional data from the National College Graduate Employment Survey (CGGES) conducted by the Institute of Economics of Education at Peking University. The analytical sample encompasses three waves of national surveys from 2019, 2021, and 2023, capturing dynamic labor market shifts during China’s industrial transformation. A multi-stage stratified sampling method was adopted to ensure a nationally representative sample, resulting in a final dataset of 9,919 engineering graduates across diverse institutional types, academic levels, and geographic regions. Measurement of skill mismatch is achieved through a sophisticated integration of micro-level survey data and international occupational benchmarks. On the supply side, graduates self-assessed their competency gains during higher education across cognitive, technical, and relational domains. On the demand side, skill requirement scores for graduates’ specific job positions were extracted from the O*NET database. Graduates’ job titles were mapped to ONET occupational codes through a systematic cross-walk procedure based on job descriptions. To ensure comparability between these sources, raw scores for both possessed and required skills were standardized and converted into percentiles. The Skill Mismatch Index was then constructed by calculating the difference between these percentiles, where a non-zero value indicates either over-skilled or skill under-skilled. To provide a more reliable estimate, we employ a fixed-effects strategy that accounts for unobserved variations across schools and year fixed effects. Specifically, we use this to examine how skill mismatch affects graduates' wages. For job satisfaction, we apply a Fixed-Effect Ordered Logit model to respect its ordinal nature. By controlling for school and year fixed effects, the study effectively isolates the impact of skill mismatch from other confounding socio-economic variables, ensuring the robustness of the parameter estimations.

It is found that skill mismatch exerts a significant negative impact on the initial wages of Chinese engineering graduates between 2019 and 2023, reflecting a substantial productivity loss consistent with Human Capital Theory. However, the psychological outcomes regarding job satisfaction present a more nuanced narrative. While Person-Job Fit theory suggests a decline in satisfaction due to environmental misalignment, this study identifies a compensatory mechanism through Self-Determination Theory (SDT). Specifically, it is expected that when workplace environments fulfill basic psychological needs—such as autonomy and competence—the resulting intrinsic motivation can act as a buffer, mitigating the adverse effects of mismatch on professional well-being. By integrating these competing perspectives, the study fills a critical void in the sparse literature concerning engineering-specific career outcomes and challenges the monolithic view of mismatch as an entirely negative phenomenon in the modern technological landscape. Beyond its theoretical contributions, the findings offer vital practical implications for stakeholders in engineering education and policy. To ensure that competency gains in higher education translate effectively into workplace productivity, institutions must foster deep integration between academia and industry, ensuring that curricula align with real-time industrial demands. Furthermore, career counseling services should be reformed to guide students in constructing realistic career expectations while emphasizing the alignment of psychological needs with job roles. Ultimately, policymakers can leverage standardized tools—such as the O*NET benchmarking utilized in this research—to establish dynamic skill-monitoring systems. Such measures would facilitate a more efficient bridge between educational supply and the evolving requirements of the labor market, promoting a more sustainable and high-quality transition for engineering talent.

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