研究生: |
林龍信 Lung-Hsin Lin |
---|---|
論文名稱: |
工作4.0時代人才留用的全面探索:改良模糊AHP與模糊DEMATEL方法論 A Comprehensive Exploration of Talent Retention for Work 4.0: An Improved Fuzzy AHP and Fuzzy DEMATEL Methodology |
指導教授: |
王孔政
Kung-Jeng Wang |
口試委員: |
王孔政
歐陽超 蔣明晃 張秉宸 何秀青 |
學位類別: |
博士 Doctor |
系所名稱: |
管理學院 - 管理研究所 Graduate Institute of Management |
論文出版年: | 2024 |
畢業學年度: | 113 |
語文別: | 英文 |
論文頁數: | 105 |
中文關鍵詞: | 模糊層級分析法 、模糊決策實驗室分析法 、多準則決策分析 、人才留用 、工作4.0 |
外文關鍵詞: | Fuzzy analytical hierarchy process (FAHP), Fuzzy decision-making trial and evaluation laboratory (DEMATEL), Multi-criteria decision-making (MCDM), Talent retention, Work 4.0 |
相關次數: | 點閱:15 下載:0 |
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在快速發展的Work 4.0環境中,如何制定有效的人才留用關鍵策略的需求,亟待探討。Work 4.0環境的特點在於數位化、全球化及靈活工作安排的融合。儘管近期文獻已探討這些因素如何重塑傳統的雇傭關係,但對於人才留用相關挑戰的具體理解,仍存在顯著的缺口。
本論文旨在通過探討各種人才留用準則之間的因果關係,並根據其在Work 4.0環境中的影響進行優先排序。本研究採用多階段的方法框架,結合模糊層級分析法、模糊決策實驗室分析法及相似性整合法。這一方法能夠全面評估諸如「薪酬與福利」、「職能匹配」、「工作與生活平衡」、「獎勵與認可」、以及「晉升與成長機會」等因素之間的相互依賴關係。這些準則對於在數位時代制定強化人才留用的策略至關重要。此外,本研究透過開發創新演算法,提高了模糊層級分析法、模糊決策實驗室分析法及相似性整合法的效率與透明度,從而確保了準則評估的準確性,並更好地可視化準則之間的相互關係。
此外,本研究揭櫫基於績效的薪酬、靈活工作安排及終身學習等因素,做為有效人才留用管理的關鍵原則。透過將人才留用策略與人才偏好及技術進步相結合,本研究為組織提供了一個提升人才留用的策略路徑,以應對動態的Work 4.0環境。研究結果顯示,「人員」對人才留用的影響最大,其次是「技術」和「流程」。特別是「薪酬與福利」、「認知一致性」及「數位化知識管理」成為組織在數位化工作環境中人才留用的首要優先事項。
本研究提出一個針對Work 4.0環境量身定制的概念性人才留用框架,為人力資源專業人士及政策制定者提供了實用工具,以將人才留用策略與不斷變化的員工偏好相契合。尤其是在Work 4.0時代,強調人才留用準則在塑造組織人才管理策略中的關鍵作用。
最後,本研究提出了一個全面的戰略性人才留用模型,旨在加強人才留用,提高先進人力資源管理實踐在數位時代的有效性。通過此一個完整的方法框架和概念性人才留用模型,本研究填補了既有文獻的缺漏,幫助組織應對Work 4.0環境中人才留用的複雜性。這些洞察為制定量身定制的人才留用策略提供相對應的指導,以確保長期的人才可持續性及競爭力。
This study addresses the critical need for effective Talent Retention (TR) strategies in the rapidly evolving Work 4.0 environment, characterized by the integration of digitalization, globalization, and flexible work arrangements. Although recent literature has explored how these factors are reshaping traditional employment relationships, a significant gap remains in understanding the specific challenges associated with TR. This dissertation aims to fill that gap by investigating the causal relationships among various TR criteria and prioritizing them based on their influence within the Work 4.0 context.
To address this issue, the research utilizes a multi-stage methodological framework, integrating the Fuzzy Analytical Hierarchy Process (FAHP), Decision-Making Trial and Evaluation Laboratory (DEMATEL), and the Similarity Aggregation Method (SAM). This approach allows for a comprehensive evaluation of the interdependencies among factors such as "compensation & benefits", "competency mapping", "work-life balance", "reward & recognition", and promotion & opportunities for growth". These criteria are essential for developing strategies that enhance TR in the digital era. Additionally, the study contributes to human resource development by developing innovative algorithms that improve the efficiency and transparency of the FAHP, DEMATEL, and SAM methods, ensuring more accurate criteria evaluation and better visualization of inter-criteria relationships.
The research also highlights the importance of performance-based compensation, flexible work arrangements, and lifelong learning as key principles in effective TR management. By aligning TR strategies with talent preferences and technological advancements, the study offers organizations a strategic roadmap for enhancing workforce retention in the dynamic Work 4.0 landscape. Key findings indicate that "people" have the most significant influence on TR, followed by "technology" and "process." In particular, "compensation & benefits", "perception congruence", and "knowledge management with digitalization" emerge as top priorities for organizations aiming to retain talent in a digitalized work environment. The study introduces a conceptual TR framework tailored to the Work 4.0 context, providing HR professionals and policymakers with practical tools to align TR strategies with evolving workforce preferences. It underscores the pivotal role of TR criteria in shaping organizational strategies for talent management in Work 4.0. Ultimately, this research presents a comprehensive strategic TR model designed to strengthen talent retention efforts and improve the effectiveness of advanced human resource management practices in the digital age.
By proposing a robust methodological framework and conceptual TR model, this study fills a critical gap in the literature, helping organizations navigate the complexities of talent retention in Work 4.0. The insights provided valuable guidance for developing tailored TR strategies, ensuring long-term workforce sustainability and competitiveness. Notably, the findings make a significant contribution to human resource development, offering empirical insights to support the creation of forward-looking policies and strategies that foster a resilient and skilled workforce in an ever-evolving landscape.
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