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題名 人工智慧專利與企業市值之關聯：來自半導體產業的實證分析
Artificial Intelligence Patents and Corporate Market Value: Evidence from the Semiconductor Industry
作者 萬文皓
Wan, Wen-Hao
貢獻者 楊宗翰
萬文皓
Wan, Wen-Hao
關鍵詞 人工智慧
專利
公司市值
公司年齡
資本支出
調節效果
Artificial intelligence
Patent
Market value
Firm age
Capital expenditures
Moderating effect
日期 2025
上傳時間 1-Sep-2025 16:07:42 (UTC+8)
摘要 隨著人工智慧（AI）技術快速發展，企業對AI技術的投入成為提升競爭力的重要策略之一，然而AI投入對公司市值的實際影響仍需進一步實證討論，並且不同公司年齡與資本支出是否會產生調節效果也值得探究。本研究以半導體產業（SIC 3674）2014年至2024年之81家上市公司為研究對象，利用World Intellectual Property Organization (WIPO)專利資料庫取得各公司AI相關專利數量，作為AI投入的代理變數，且納入公司年齡及資本支出作為調節變數，並以公司市值作為衡量指標，探討AI投入對公司市值之影響。 實證結果顯示，AI投入對公司市值具有正向且顯著的影響，且在公司年齡較大的企業中，AI投入對市值的影響效果更為顯著，然而當企業資本支出較高時，AI 專利對市值的邊際正向效果越弱。本研究結果有助於企業釐清AI投入對公司市值的實際效益，並提供管理階層在AI投資決策上的參考。
With the rapid advancement of artificial intelligence (AI) technologies, investment in AI has become a key strategy for enhancing corporate competitiveness. However, the actual impact of AI investment on firm market value remains to be further empirically examined, and it is also worth investigating whether firm age and capital expenditures have moderating effects on this relationship. This study focuses on 81 publicly listed companies in the semiconductor industry (SIC 3674) from 2014 to 2024, using data from the World Intellectual Property Organization (WIPO) patent database to obtain the number of AI-related patents for each company as a proxy for AI investment. Firm age and capital expenditures are incorporated as moderating variables, and firm market value serves as the primary performance indicator to explore the effect of AI investment on firm market value. The empirical results indicate that AI investment has a positive and significant impact on firms’ market value, with the effect being more pronounced in older firms. However, when capital expenditures are higher, the marginal positive effect of AI patents on market value becomes weaker. These findings help clarify the actual benefits of AI investment for firms’ market value and provide useful implications for managerial decision-making regarding AI-related investments.
參考文獻 Amuru, D., Zahra, A., Vudumula, H. V., Cherupally, P. K., Gurram, S. R., Ahmad, A., & Abbas, Z. (2023). AI/ML algorithms and applications in VLSI design and technology. Integration, 93, 102048. Balasubramanian, N., & Lee, J. (2008). Firm age and innovation. Industrial and Corporate Change, 17(5), 1019-1047. Barney, J. (1991). Firm resources and sustained competitive advantage. Journal of Management, 17(1), 99-120. Chen, J., Lim, C. P., Tan, K. H., Govindan, K., & Kumar, A. (2021). Artificial intelligence-based human-centric decision support framework: an application to predictive maintenance in asset management under pandemic environments. Annals of Operations Research, 1-24. Coad, A., Segarra, A., & Teruel, M. (2016). Innovation and firm growth: does firm age play a role? Research Policy, 45(2), 387-400. Damioli, G., Van Roy, V., Vértesy, D., & Vivarelli, M. (2024). Drivers of employment dynamics of AI innovators. Technological Forecasting and Social Change, 201, 123249. Dang, C., Li, Z. F., & Yang, C. (2018). Measuring firm size in empirical corporate finance. Journal of Banking & Finance, 86, 159-176. Filieri, R., D’Amico, E., Destefanis, A., Paolucci, E., & Raguseo, E. (2021). Artificial intelligence (AI) for tourism: an European-based study on successful AI tourism start-ups. International Journal of Contemporary Hospitality Management, 33(11), 4099-4125. Hall, B. H., Jaffe, A. B., & Trajtenberg, M. (2000). Market value and patent citations: A first look. In: national bureau of economic research Cambridge, Mass., USA. Harford, J. (1999). Corporate cash reserves and acquisitions. The Journal of Finance, 54(6), 1969-1997. Henderson, R. M., & Clark, K. B. (1990). Architectural innovation: The reconfiguration of existing product technologies and the failure of established firms. Administrative Science Quarterly, 9-30. Huang, C.-K., Wang, T., & Huang, T.-Y. (2020). Initial evidence on the impact of big data implementation on firm performance. Information Systems Frontiers, 22(2), 475-487. Huergo, E., & Jaumandreu, J. (2004). Firms' age, process innovation and productivity growth. International Journal of Industrial Organization, 22(4), 541-559. Jensen, M. C. (1986). Agency costs of free cash flow, corporate finance, and takeovers. The American Economic Review, 76(2), 323-329. Kim, T., Park, Y., & Kim, W. (2022, August). The impact of artificial intelligence on firm performance. In 2022 Portland International Conference on Management of Engineering and Technology (PICMET) (pp. 1-10). IEEE. Kopka, A., & Fornahl, D. (2024). Artificial intelligence and firm growth—catch-up processes of SMEs through integrating AI into their knowledge bases. Small Business Economics, 62(1), 63-85. Levitt, B., & March, J. G. (1988). Organizational learning. Annual Review of Sociology, 14(1), 319-338. Petruzzelli, A. M., Ardito, L., & Savino, T. (2018). Maturity of knowledge inputs and innovation value: The moderating effect of firm age and size. Journal of Business Research, 86, 190-201. Raisch, S., & Krakowski, S. (2021). Artificial intelligence and management: The automation–augmentation paradox. Academy of Management Review, 46(1), 192-210. Richardson, S. (2006). Over-investment of free cash flow. Review of Accounting Studies, 11, 159-189. Titman, S., Wei, K. J., & Xie, F. (2004). Capital investments and stock returns. Journal of Financial and Quantitative Analysis, 39(4), 677-700. Trajtenberg, M. (2018). AI as the next GPT: a Political-Economy Perspective (No. w24245). National Bureau of Economic Research. Van Roy, V., Vértesy, D., & Vivarelli, M. (2018). Technology and employment: Mass unemployment or job creation? Empirical evidence from European patenting firms. Research Policy, 47(9), 1762-1776. Webb, M., Short, N., Bloom, N., & Lerner, J. (2018). Some Facts of High-tech Patenting (No. w24793). National Bureau of Economic Research. Wei, R., & Pardo, C. (2022). Artificial intelligence and SMEs: How can B2B SMEs leverage AI platforms to integrate AI technologies? Industrial Marketing Management, 107, 466-483. Wernerfelt, B. (1984). A resource‐based view of the firm. Strategic Management Journal, 5(2), 171-180. WIPO. (2019). WIPO technology trends 2019: Artificial intelligence. Geneva: World Intellectual Property Organization. Yang, C.-H. (2022). How artificial intelligence technology affects productivity and employment: firm-level evidence from Taiwan. Research Policy, 51(6), 104536.
描述 碩士
國立政治大學
科技管理與智慧財產研究所
112364133
資料來源 http://thesis.lib.nccu.edu.tw/record/#G0112364133
資料類型 thesis
dc.contributor.advisor 楊宗翰zh_TW
dc.contributor.author (Authors) 萬文皓zh_TW
dc.contributor.author (Authors) Wan, Wen-Haoen_US
dc.creator (作者) 萬文皓zh_TW
dc.creator (作者) Wan, Wen-Haoen_US
dc.date (日期) 2025en_US
dc.date.accessioned 1-Sep-2025 16:07:42 (UTC+8)-
dc.date.available 1-Sep-2025 16:07:42 (UTC+8)-
dc.date.issued (上傳時間) 1-Sep-2025 16:07:42 (UTC+8)-
dc.identifier (Other Identifiers) G0112364133en_US
dc.identifier.uri (URI) https://nccur.lib.nccu.edu.tw/handle/140.119/159255-
dc.description (描述) 碩士zh_TW
dc.description (描述) 國立政治大學zh_TW
dc.description (描述) 科技管理與智慧財產研究所zh_TW
dc.description (描述) 112364133zh_TW
dc.description.abstract (摘要) 隨著人工智慧（AI）技術快速發展，企業對AI技術的投入成為提升競爭力的重要策略之一，然而AI投入對公司市值的實際影響仍需進一步實證討論，並且不同公司年齡與資本支出是否會產生調節效果也值得探究。本研究以半導體產業（SIC 3674）2014年至2024年之81家上市公司為研究對象，利用World Intellectual Property Organization (WIPO)專利資料庫取得各公司AI相關專利數量，作為AI投入的代理變數，且納入公司年齡及資本支出作為調節變數，並以公司市值作為衡量指標，探討AI投入對公司市值之影響。 實證結果顯示，AI投入對公司市值具有正向且顯著的影響，且在公司年齡較大的企業中，AI投入對市值的影響效果更為顯著，然而當企業資本支出較高時，AI 專利對市值的邊際正向效果越弱。本研究結果有助於企業釐清AI投入對公司市值的實際效益，並提供管理階層在AI投資決策上的參考。zh_TW
dc.description.abstract (摘要) With the rapid advancement of artificial intelligence (AI) technologies, investment in AI has become a key strategy for enhancing corporate competitiveness. However, the actual impact of AI investment on firm market value remains to be further empirically examined, and it is also worth investigating whether firm age and capital expenditures have moderating effects on this relationship. This study focuses on 81 publicly listed companies in the semiconductor industry (SIC 3674) from 2014 to 2024, using data from the World Intellectual Property Organization (WIPO) patent database to obtain the number of AI-related patents for each company as a proxy for AI investment. Firm age and capital expenditures are incorporated as moderating variables, and firm market value serves as the primary performance indicator to explore the effect of AI investment on firm market value. The empirical results indicate that AI investment has a positive and significant impact on firms’ market value, with the effect being more pronounced in older firms. However, when capital expenditures are higher, the marginal positive effect of AI patents on market value becomes weaker. These findings help clarify the actual benefits of AI investment for firms’ market value and provide useful implications for managerial decision-making regarding AI-related investments.en_US
dc.description.tableofcontents 第一章　緒論 1 第一節　研究動機 1 第二節　研究目的 3 第二章　文獻探討 5 第一節　資源基礎觀點 5 第二節　AI投入與公司市值 6 第三節　公司年齡與調節效果 8 第四節　資本支出與調節效果 9 第五節　文獻小結 10 第三章　研究方法 12 第一節　研究樣本與資料來源 12 第二節　研究架構 13 第三節　研究變數定義與衡量 14 第四節　研究模型 17 第四章　實證結果 21 第一節　敘述性統計分析 21 第二節　變數相關矩陣分析 23 第三節　實證結果與分析 26 第五章　結論與建議 33 第一節　研究結論 33 第二節　研究限制 34 第三節　研究建議 36 參考文獻 38zh_TW
dc.format.extent 1028347 bytes-
dc.format.mimetype application/pdf-
dc.source.uri (資料來源) http://thesis.lib.nccu.edu.tw/record/#G0112364133en_US
dc.subject (關鍵詞) 人工智慧zh_TW
dc.subject (關鍵詞) 專利zh_TW
dc.subject (關鍵詞) 公司市值zh_TW
dc.subject (關鍵詞) 公司年齡zh_TW
dc.subject (關鍵詞) 資本支出zh_TW
dc.subject (關鍵詞) 調節效果zh_TW
dc.subject (關鍵詞) Artificial intelligenceen_US
dc.subject (關鍵詞) Patenten_US
dc.subject (關鍵詞) Market valueen_US
dc.subject (關鍵詞) Firm ageen_US
dc.subject (關鍵詞) Capital expendituresen_US
dc.subject (關鍵詞) Moderating effecten_US
dc.title (題名) 人工智慧專利與企業市值之關聯：來自半導體產業的實證分析zh_TW
dc.title (題名) Artificial Intelligence Patents and Corporate Market Value: Evidence from the Semiconductor Industryen_US
dc.type (資料類型) thesisen_US
dc.relation.reference (參考文獻) Amuru, D., Zahra, A., Vudumula, H. V., Cherupally, P. K., Gurram, S. R., Ahmad, A., & Abbas, Z. (2023). AI/ML algorithms and applications in VLSI design and technology. Integration, 93, 102048. Balasubramanian, N., & Lee, J. (2008). Firm age and innovation. Industrial and Corporate Change, 17(5), 1019-1047. Barney, J. (1991). Firm resources and sustained competitive advantage. Journal of Management, 17(1), 99-120. Chen, J., Lim, C. P., Tan, K. H., Govindan, K., & Kumar, A. (2021). Artificial intelligence-based human-centric decision support framework: an application to predictive maintenance in asset management under pandemic environments. Annals of Operations Research, 1-24. Coad, A., Segarra, A., & Teruel, M. (2016). Innovation and firm growth: does firm age play a role? Research Policy, 45(2), 387-400. Damioli, G., Van Roy, V., Vértesy, D., & Vivarelli, M. (2024). Drivers of employment dynamics of AI innovators. Technological Forecasting and Social Change, 201, 123249. Dang, C., Li, Z. F., & Yang, C. (2018). Measuring firm size in empirical corporate finance. Journal of Banking & Finance, 86, 159-176. Filieri, R., D’Amico, E., Destefanis, A., Paolucci, E., & Raguseo, E. (2021). Artificial intelligence (AI) for tourism: an European-based study on successful AI tourism start-ups. International Journal of Contemporary Hospitality Management, 33(11), 4099-4125. Hall, B. H., Jaffe, A. B., & Trajtenberg, M. (2000). Market value and patent citations: A first look. In: national bureau of economic research Cambridge, Mass., USA. Harford, J. (1999). Corporate cash reserves and acquisitions. The Journal of Finance, 54(6), 1969-1997. Henderson, R. M., & Clark, K. B. (1990). Architectural innovation: The reconfiguration of existing product technologies and the failure of established firms. Administrative Science Quarterly, 9-30. Huang, C.-K., Wang, T., & Huang, T.-Y. (2020). Initial evidence on the impact of big data implementation on firm performance. Information Systems Frontiers, 22(2), 475-487. Huergo, E., & Jaumandreu, J. (2004). Firms' age, process innovation and productivity growth. International Journal of Industrial Organization, 22(4), 541-559. Jensen, M. C. (1986). Agency costs of free cash flow, corporate finance, and takeovers. The American Economic Review, 76(2), 323-329. Kim, T., Park, Y., & Kim, W. (2022, August). The impact of artificial intelligence on firm performance. In 2022 Portland International Conference on Management of Engineering and Technology (PICMET) (pp. 1-10). IEEE. Kopka, A., & Fornahl, D. (2024). Artificial intelligence and firm growth—catch-up processes of SMEs through integrating AI into their knowledge bases. Small Business Economics, 62(1), 63-85. Levitt, B., & March, J. G. (1988). Organizational learning. Annual Review of Sociology, 14(1), 319-338. Petruzzelli, A. M., Ardito, L., & Savino, T. (2018). Maturity of knowledge inputs and innovation value: The moderating effect of firm age and size. Journal of Business Research, 86, 190-201. Raisch, S., & Krakowski, S. (2021). Artificial intelligence and management: The automation–augmentation paradox. Academy of Management Review, 46(1), 192-210. Richardson, S. (2006). Over-investment of free cash flow. Review of Accounting Studies, 11, 159-189. Titman, S., Wei, K. J., & Xie, F. (2004). Capital investments and stock returns. Journal of Financial and Quantitative Analysis, 39(4), 677-700. Trajtenberg, M. (2018). AI as the next GPT: a Political-Economy Perspective (No. w24245). National Bureau of Economic Research. Van Roy, V., Vértesy, D., & Vivarelli, M. (2018). Technology and employment: Mass unemployment or job creation? Empirical evidence from European patenting firms. Research Policy, 47(9), 1762-1776. Webb, M., Short, N., Bloom, N., & Lerner, J. (2018). Some Facts of High-tech Patenting (No. w24793). National Bureau of Economic Research. Wei, R., & Pardo, C. (2022). Artificial intelligence and SMEs: How can B2B SMEs leverage AI platforms to integrate AI technologies? Industrial Marketing Management, 107, 466-483. Wernerfelt, B. (1984). A resource‐based view of the firm. Strategic Management Journal, 5(2), 171-180. WIPO. (2019). WIPO technology trends 2019: Artificial intelligence. Geneva: World Intellectual Property Organization. Yang, C.-H. (2022). How artificial intelligence technology affects productivity and employment: firm-level evidence from Taiwan. Research Policy, 51(6), 104536.zh_TW