隨著數位轉型與技術快速發展，臺灣作為以高科技產業為主的出口導向型經濟體，其勞動市場變化值得關注。本研究結合2020至2023年《人力運用調查》原始資料，與多項衡量科技化程度之資料建構成的相關產業科技化指標，運用普通最小平方法(OLS)、Heckman選擇性偏誤修正法及Blinder-Oaxaca薪資分解法，探討產業科技化程度對臺灣私部門STEM與非STEM勞工薪資影響與其薪資差異的來源。 本文結果發現，產業科技化程度對勞工薪資均具正向效果，對非STEM勞工尤為顯著。STEM與非STEM勞工的薪資差異主要來自於個人特性與工作特性，數位化程度則有助於縮小兩者差距；但在藍領與女性勞工中，數位化程度反而擴大薪資差異。此外，機器自動化對電子產業的勞工薪資負面衝擊尤為明顯。因此，建議政府持續鼓勵與支持產業的研發創新，以提升STEM人力的生產力與薪資成長空間；對非STEM則應強化數位技能與跨域能力的培訓，並聚焦受負面衝擊較顯著的群體，建立人力影響評估與預警機制，以協助勞工適應數位轉型。;As digital transformation and technological advancement accelerate, Taiwan—an export-oriented economy driven by high-tech industries—faces noteworthy changes in its labor market. This study integrates data from the 2020 to 2023 Manpower Utilization Survey and various relevant indicators measuring industrial technological advancement that was constructed from different sources that to construct. Using Ordinary Least Squares (OLS), the Heckman Selection Bias Correction Model, and the Blinder-Oaxaca wage decomposition methods, this research examines the impact of industrial technological advancement on the wage determination of private-sector STEM and non-STEM workers in Taiwan and analyzes the sources of their wage differences. The results show that digitalization positively influences wages for all workers, with a particularly strong effect on non-STEM workers. Moreover, wage differentials between STEM and non-STEM workers are primarily explained by personal and job-related characteristics, while industrial technological advancement tends to narrow this gap. However, for blue-collar and female workers, digitalization appears to widen wage differentials. In addition, industrial automation has a notably negative wage impact on workers in the electronics industry. Based on these findings, this study recommends that the government continue to promote and support industrial R&D and innovation in order to enhance the productivity and wage growth potential of STEM workers. For non-STEM workers, it is crucial to improve digital skills and interdisciplinary training. Additionally, the government should also focus on groups more vulnerable to negative impacts by establishing workforce impact assessments and early warning mechanisms to help workers adapt to digital transformation.
