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    Title: AI新創軟體企業的動態能力之分析 - 以A公司為例
    An Analysis of the Dynamics Capabilities of AI Software Startups – A Case Study of A Company
    Authors: 林立祺
    Lin, Li-Qi
    Contributors: 黃國峯
    傅浚映

    Huang, Kuo-Feng
    Fu, Jyun-Ying

    林立祺
    Lin, Li-Qi
    Keywords: 人工智慧新創
    組織生命週期
    動態能力
    製造業
    數位轉型
    台灣軟體產業
    AI startup
    Organizational life cycle
    Dynamic capabilities
    Manufacturing
    Digital transformation
    Taiwan software industry
    Date: 2025
    Issue Date: 2025-08-04 13:47:15 (UTC+8)
    Abstract: 在AI技術快速演進與製造業數位轉型需求驅動下,台灣本土AI新創企業近年逐步浮現。然而,多數AI新創面臨資源稀缺、產業理解門檻高與市場教育成本高昂等多重挑戰,缺乏系統化探討其如何發展出因應變局之能力與策略。
    本研究聚焦於台灣製造業AI應用領域之新創企業,以A公司為個案,探討其自2018年創立以來,在面對高度不確定性與結構性壓力下,如何藉由動態能力展現組織韌性並逐步發展成具備制度規模之企業。
    本研究以質性研究為方法,透過次級資料分析與半結構式訪談蒐集資料,並運用三大理論架構進行分析:(1)Porter(1980)之五力分析模型,檢視個案公司創業初期所面臨之產業結構挑戰;(2)Quinn與Cameron(1983)之組織生命週期理論,梳理其於不同成長階段的組織與策略轉變;(3)Teece(2007)之動態能力理論,分析其如何透過感知(sensing)、掌握(seizing)與再配置(reconfiguring)三構面,持續回應外部環境變化與技術浪潮衝擊。
    研究發現如下:
    (一)A公司於創業初期具備明確市場定位與創辦人深厚產業網絡,成功建立初始競爭優勢,並於產業中低競爭、高教育成本的不對稱結構下迅速切入利基市場
    (二)隨企業進入不同發展階段,組織結構歷經從創業期的扁平夥伴制、集體成長期的流程制度化,到正式化與控制期的治理規範強化與國際化佈局,展現高度調適彈性與組織自覺;
    (三)面對地緣政治、生成式AI技術變革與全球製造場域轉移壓力,A公司能主動感知產業變化,靈活整合資源與產品模組(如AutoML、AILM、GenAI)並轉型為Domain Twin解決方案供應商,展現出強韌的動態能力與市場回應速度。
    本研究不僅填補AI新創企業成長歷程與策略變化相關文獻之不足,亦提供新創經營者在高變動產業中建立差異化定位與策略靈活性之實務啟示,對政策制定者與投資人亦具備產業評估與生態建構之參考價值。
    Driven by the rapid advancement of AI technologies and the rising demand for digital transformation in the manufacturing sector, domestic AI startups in Taiwan have increasingly emerged in recent years. However, most of these startups face multiple challenges, including scarce resources, high industry entry barriers, and substantial market education costs.
    There remains a lack of systematic exploration regarding how these enterprises develop the capabilities and strategies needed to navigate such turbulent environments.
    This study focuses on AI startups operating in the Taiwanese manufacturing sector, using Company A as a case study.
    It explores how, since its establishment in 2018, the company has demonstrated organizational resilience and evolved into a structurally scaled enterprise by leveraging dynamic capabilities amid high uncertainty and structural pressure.
    Adopting a qualitative research approach, this study collects data through secondary source analysis and semi-structured interviews. It draws on three theoretical frameworks:
    (1) Porter’s (1980) Five Forces Framework to examine the industrial structural pressures faced by the company during its early stage;
    (2) the Organizational Life Cycle Model by Quinn and Cameron (1983) to trace the company's organizational and strategic transformations across different growth stages; and
    (3) Teece’s (2007) Dynamic Capabilities Framework to analyze how the company has responded to environmental changes and technological disruption through sensing, seizing, and reconfiguring.
    The research yields the following key findings:
    (1) In its early stage, Company A established a clear market positioning and leveraged the founders’ extensive industry networks to gain initial competitive advantage. It successfully entered a niche market within an industry characterized by low competition but high market education costs and asymmetries.
    (2) As the company progressed through different development phases, its organizational structure evolved—from a flat, partner-oriented model in the entrepreneurial stage, to institutionalized processes during the collective growth stage, and eventually to formalized governance and international expansion during the control stage—demonstrating high adaptability and organizational awareness.
    (3) In response to geopolitical shifts, the rise of generative AI technologies, and the relocation of global manufacturing hubs, the company proactively sensed changes, reallocated resources, and integrated product modules (such as AutoML, AILM, and GenAI), ultimately transforming into a Domain Twin solution provider. This reflects the company's robust dynamic capabilities and agile market responsiveness.
    This study fills a gap in the literature regarding the growth trajectory and strategic evolution of AI startups, while also offering practical implications for startup leaders seeking to establish differentiated positioning and strategic flexibility in rapidly changing industries. Moreover, the findings provide valuable insights for policymakers and investors engaged in industry assessment and ecosystem development.
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    Description: 碩士
    國立政治大學
    企業管理研究所(MBA學位學程)
    112363075
    Source URI: http://thesis.lib.nccu.edu.tw/record/#G0112363075
    Data Type: thesis
    Appears in Collections:[企業管理研究所(MBA學位學程)] 學位論文

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