本研究在探討影響製造業技藝有關人員對創新技術產生抵制心理的關鍵因素，並以創新阻力理論(Innovation Resistance Theory, IRT)為理論基礎，透過質性個案研究深入分析技藝人員在面對CNC電腦數值控制技術導入時的認知與行為反應。相較於大量文獻聚焦於創新採用(TAM)，本研究關注創新導入的抗拒歷程與形成機制，試圖填補目前學界對於技藝人員抗拒心理之理解不足處。
研究方法上，本研究採用質性研究策略，透過半結構式深度訪談蒐集某中南部具代表性之金屬切削加工企業(千暉機械股份有限公司)中十二位具備實作經驗的CNC技藝人員之觀點。訪談資料依據IRT三大構面進行編碼與主題分析，包含感知創新特徵(相對優勢、相容性、複雜性)、技藝人員特徵(變革程度、性格特徵、對技術需求認知)與傳播機制特徵（資訊來源可信度、技術導入的推廣方法、資訊清晰度）。
研究發現指出：首先，技藝人員若能明確感受新技術帶來的效率提升與職涯助益，會傾向主動學習並降低初期抗拒；相反地，若新技術與現有流程不相容或操作困難，將顯著提升其抗拒程度。其次，對技術需求具備清楚認知的工人，較能有效克服學習門檻，顯示技術認知與變革意願比個人性格特徵更能左右其抗拒行為。第三，有效的技術傳播機制如面對面教學、師徒制度與組織制度化支持，能顯著降低資訊不確定性與心理排斥感，進而提升接受度縮短學習曲線。
綜合而言，本研究延伸了創新阻力理論的應用場域，證實其可作為觀察製造業現場技術導入困境之有效框架，並提出可用來評估新技術導入可行性的初步模式，作為企業在推動技術轉型時之參考依據。最後，管理實務上建議企業應強化員工導入前的技術認知與心理建設，提供個別化學習資源與制度支持，以減輕現場工人之抗拒心理，提升整體導入成功率。

This study investigates the key factors that influence resistance to innovative technologies among skilled workers in the manufacturing industry. Grounded in the Innovation Resistance Theory (IRT), this research adopts a qualitative case study approach to analyze the cognitive and behavioral responses of workers during the implementation of Computer Numerical Control (CNC) technology. In contrast to the large body of literature focusing on innovation adoption models such as the Technology Acceptance Model (TAM), this study emphasizes the early-stage resistance process and its formation mechanism, aiming to fill the existing theoretical gap concerning the resistance psychology of technical workers.
Methodologically, this study employs a qualitative research strategy by conducting semi-structured, in-depth interviews with twelve experienced CNC technicians from a representative metal-cutting manufacturing company in southern Taiwan (Chian-Hwei Machinery Co., Ltd.). The interview data were coded and analyzed thematically based on the three core dimensions of IRT: perceived innovation characteristics (relative advantage, compatibility, complexity), worker characteristics (degree of change, personality traits, and awareness of technical needs), and communication mechanism characteristics (credibility of information sources, promotion strategies, and clarity of information).
The findings reveal three major insights. First, when workers clearly perceive the efficiency improvements and career benefits of a new technology, they are more likely to engage in proactive learning and exhibit lower initial resistance. Conversely, incompatibility with existing workflows or operational difficulty significantly increases their resistance. Second, workers with a strong awareness of technical demands are more capable of overcoming learning barriers, suggesting that cognitive recognition of innovation and willingness to adapt are more influential than personality traits in shaping resistance behaviors. Third, effective communication mechanisms—such as face-to-face instruction, mentoring systems, and institutionalized organizational support—significantly reduce informational uncertainty and psychological rejection, thereby enhancing acceptance and shortening the learning curve.
In conclusion, this study extends the application of IRT to industrial settings, demonstrating its utility as a framework for understanding resistance in technology implementation on the shop floor. It also proposes a preliminary model to evaluate the feasibility of new technology adoption, offering practical recommendations for enterprises to enhance workers' technical awareness and psychological readiness through personalized training and systemic support, thereby increasing the success rate of technological transformation.

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