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研究生: 林倚琳
LIN, I-LING
論文名稱: 存貨轉化製成品之效率分析-以台灣通信製造業為例
Efficiency Analysis of Inventory-to-Finished-Goods Conversion: Evidence from Taiwan's Electronic Telecommunications Manufacturing Industry
指導教授: 林泰宇
LIN, TAI-YU
黃振皓
Huang, Chen-Hao
學位類別: 碩士
Master
系所名稱: 管理學院 - 企業管理學系
Department of Business Administration
論文出版年: 2026
畢業學年度: 114
語文別: 中文
論文頁數: 61
中文關鍵詞: 資料包絡分析法存貨轉化效率商品與製成品台灣電子通信製造業
外文關鍵詞: Data Envelopment Analysis, DEA-Modified Dynamic One-Stage SBM Model, inventory conversion efficiency, merchandise and finished goods, Taiwan electronic telecommunications manufacturing industry
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  • 隨著全球通信技術快速的變化,台灣電子通信製造業在全球供應鏈中有重要地位,台灣電子通信企業深耕全球通信設備的研發及製造,產品端包含交換器、路由器、基地台、及智慧相關設備,在全球供應鏈下台灣通信廠商雖然在當中長期獲利,但同時承受了供應鏈波動及技術更換的風險,在2020年至2021年間,台灣通信製造業經歷了疫情爆發、遠距辦公使得市場設備需求大增,後期隨著疫情趨緩設備需求驟降再加上中美貿易所產生的供應鏈重組影響,前期所累積的存貨無法及時消化,因此從2022年至2024年企業開始消化庫存的趨勢對整個通信產業造成衝擊。
    本研究以台灣上市電子通信製造業為研究對象,選取34家通信製造商為企業樣本採用SBM模型,針對2020年至2024年五個年度之存貨轉製成品效率進行分析,以不動產、廠房及設備成本做為跨期變數、使用權資產與營業成本為投入變數,再以存貨、商品及製成品與其他收入作為產出變數,評估各樣本企業在供應鏈資源配置與存貨轉化過程中的相對效率表現。
    實證結果顯示34家樣本企業五年總效率平均為0.643,整體資源配置效率偏低存在大量進步空間,在2021年因疫情帶動需求而達到最高點,後疫情趨緩連續三年呈現下滑,在投入變數中營業成本效率最為穩定,使用權資產效率為最差持續下跌,顯示企業使用權資產上的配置有待改善,在產出變數中存貨效率最佳代表企業維持著有效的存貨管理,商品與製成品效率為最差是企業改善空間很大的部分,其他收入則是逐年穩定成長顯示電子通信製造產業正在逐漸從代工轉為多元產出的模式。
    研究結果顯示效率高低與企業規模無直接關聯,資源配置才是決定效率的關鍵,台灣電子通信製造業的存貨管理能力優於成品交付能力,提升轉換效率是產業目前可以改善的方向,也是目前供應鏈中所遇到問題,本研究觀察期因企業消除庫存的壓力下呈持續下滑,發現存貨跨年度轉化效率與整體景氣存在高度連動關係。

    This study evaluates the inventory-to-finished-goods conversion efficiency of 34 Taiwanese electronic telecommunications manufacturers from 2020 to 2024 using a dynamic DEA Slacks-Based Measure (SBM) model. The results reveal a five-year average efficiency score of 0.643, following an inverted U-shaped trend that peaked in 2021 due to pandemic-driven demand and bottomed in 2024 amid inventory destocking pressures.
    A critical structural weakness within the industry's supply chain is identified: while firms excel in upstream inventory management (efficiency 0.959), they struggle significantly with converting that inventory into deliverable finished goods (0.809). Quadrant analysis further confirms that high inventory sufficiency does not guarantee effective downstream delivery.Finally, the findings demonstrate that firm size does not dictate efficiency, rather resource allocation capability is the decisive factor. For industry practitioners, the greatest opportunity for improvement lies in bridging the conversion gap between inventory and finished goods, underpinned by robust cost management.

    摘要 ii 誌謝 vii 表目錄 x 圖目錄 xi 第一章 緒論 1 第一節 研究背景與動機 1 第二節 研究目的 2 第三節 研究流程 4 第二章 文獻回顧 5 第一節 電子通信製造業供應鏈管理與存貨控管之效率回顧 6 第二節 存貨與成品之間的相關文獻 8 第三節 成品於電子通信製造業效率的影響 10 第三章 研究方法 13 第一節 資料包絡分析法 13 第二節 實證研究模型 13 第四章 資料分析與結果 15 第一節 資料來源、研究樣本、變數說明與研究架構 15 第二節 變數的敘述統計 19 第三節 實證結果分析 23 第五章 結論與建議 41 第一節 實證結論 41 第二節 研究建議 43 第三節 研究限制及未來研究建議 45 參考文獻 47

    Bah, A., Duramany-Lakkoh, E. K., & Daboh, F. (2023). An empirical evidence of the impact of inventory management on the profitability of manufacturing companies. JournalofAppliedFinance&Banking,13(6),207–228. https://doi.org/https://doi.org/10.47260/jafb/13610
    Charnes, A., Cooper, W. W., & Rhodes, E. (1978). Measuring the efficiency of decision making units. European journal of operational research, 2(6), 429–444. https://doi.org/10.1016/0377-2217(78)90138-8
    Chen, C.-L. (2020). Cross-disciplinary innovations by Taiwanese manufacturing SMEs in the context of Industry 4.0. Journal of Manufacturing Technology Management, 31(6), 1145–1168. https://doi.org/https://doi.org/10.1108/JMTM-08-2019-0301
    Demestichas, K., & Daskalakis, E. (2020). Information and communication technology solutionsforthecirculareconomy.Sustainability,12(18),7272. https://doi.org/10.3390/su12187272
    Fotova Čiković, K., & Lozić, J. (2022). Application of data envelopment analysis (DEA) in information and communication technologies. Tehnički glasnik, 16(1), 129–134. https://doi.org/https://doi.org/10.31803/tg-20210906103816
    Gao, D., Wang, N., Jiang, Q., & Jiang, B. (2022). Inventory management. In Enterprises’ Green Growth Model and Value Chain Reconstruction: Theory and Method (pp. 251–269). Springer. https://doi.org/https://doi.org/10.1007/978-981-19-3991-4
    George, A. S., George, A. H., & Baskar, T. (2023). Wi-Fi 7: The next frontier in wireless connectivity. Partners Universal International Innovation Journal, 1(4), 133–145. https://doi.org/https://doi.org/10.5281/zenodo.8266217
    Ghelani, H. (2024). AI-driven quality control in PCB manufacturing: Enhancing production efficiency and precision. Valley International Journal Digital Library, 12(10), 1549–1564. https://doi.org/ 10.18535/ijsrm/v12i10.ec06
    Handoyo, R. D., Ibrahim, K. H., Rismawan, L. B., Haryanto, T., Erlando, A., Sarmidi, T., Djayadi, F. V., Zaidi, M. A. S., Sethi, N., & Sylviana, W. (2024). Information communication technology and manufacturing industry exports based on technology intensity in OECD and non-OECD countries. Research in Globalization,8,100228. https://doi.org/https://doi.org/10.1016/j.resglo.2024.100228
    Hsu, S.-Y., Chiu, S.-Y., & Chiu, Y.-h. (2025). Taiwan telecommunication AI industry ESG disclosure.ScientificReports,15(1),20043. https://doi.org/https://doi.org/10.1038/s41598-025-04585-1
    Hu, J.-L., Chen, Y.-C., & Yang, Y.-P. (2022). The development and issues of energy-ICT: A review of literature with economic and managerial viewpoints. Energies, 15(2), 594. https://doi.org/ https://doi.org/10.3390/en15020594
    Ivanov, D., Tsipoulanidis, A., & Schönberger, J. (2021). Inventory management. In Global Supply Chain and Operations Management: A Decision-Oriented IntroductiontotheCreationofValue(pp.385–433).Springer. https://doi.org/https://doi.org/10.1007/978-3-030-72331-6_13
    Kumar, A., Singh, R. K., & Modgil, S. (2020). Exploring the relationship between ICT, SCM practices and organizational performance in agri-food supply chain. Benchmarking:AnInternationalJournal,27(3),1003–1041. https://doi.org/https://doi.org/10.1108/BIJ-11-2019-0500
    Li, D., Chen, Y., & Miao, J. (2022). Does ICT create a new driving force for manufacturing?—EvidencefromChinesemanufacturingfirms. TelecommunicationsPolicy,46(1),102229. https://doi.org/10.1016/j.telpol.2021.102229
    Liao, S.-H., Hu, D.-C., & Ding, L.-W. (2017). Assessing the influence of supply chain collaboration value innovation, supply chain capability and competitive advantage in Taiwan's networking communication industry. International Journal ofProductionEconomics,191,143–153. https://doi.org/10.1016/j.ijpe.2017.06.001
    Lijuan, C., Bhaumik, A., Xinfeng, W., & Jingwen, W. (2023). The effects of inventory management on business efficiency. International Journal For Multidisciplinary Research,5(4),1–17. https://doi.org/https://doi.org/10.36948/ijfmr.2023.v05i04.4877
    Mashayekhy, Y., Babaei, A., Yuan, X.-M., & Xue, A. (2022). Impact of Internet of Things (IoT) on inventory management: A literature survey. Logistics, 6(2), 33. https://doi.org/ 10.3390/logistics6020033
    Mohamed, A. E. (2024). Inventory management. In Operations Management-Recent AdvancesandNewPerspectives.IntechOpen. https://doi.org/10.5772/intechopen.113282
    Mor, R. S., Kumar, D., Yadav, S., & Jaiswal, S. K. (2021). Achieving cost efficiency through increased inventory leanness: Evidence from manufacturing industry. ProductionEngineeringArchives,27(1),42–49. https://doi.org/https://doi.org/10.30657/pea.2021.27.6.
    Oh, J., Lee, S., & Yang, J. (2015). A collaboration model for new product development through the integration of PLM and SCM in the electronics industry. Computers inIndustry,73,82–92. https://doi.org/https://doi.org/10.1016/j.compind.2015.08.003
    Panwar, A., Olfati, M., Pant, M., & Snasel, V. (2022). A Review on the 40 Years of Existence of Data Envelopment Analysis Models: Historic Development and Current Trends: A. Panwar et al. Archives of computational methods in engineering, 29(7), 5397–5426. https://doi.org/https://doi.org/10.1007/s11831-022-09770-3
    Qin, W., Chen, S., & Peng, M. (2020). Recent advances in Industrial Internet: insights and challenges. Digital Communications and Networks, 6(1), 1–13. https://doi.org/https://doi.org/10.1016/j.dcan.2019.07.001
    Ríos Villacorta, M. A., Ramos Farroñán, E. V., Alarcón García, R. E., Castro Ijiri, G. L., Bravo-Jaico, J. L., Minchola Vásquez, A. M., Ganoza-Ubillús, L. M., Escobedo Gálvez, J. F., Ríos Yovera, V. R., & Durand Gonzales, E. J. (2025). Telework for a sustainable future: Systematic review of its contribution to global corporate sustainability (2020–2024). Sustainability, 17(13), 5737. https://doi.org/ https://doi.org/10.3390/su17135737
    Song, J.-S., Van Houtum, G.-J., & Van Mieghem, J. A. (2020). Capacity and inventory management: Review, trends, and projections. Manufacturing & Service OperationsManagement,22(1),36–46. https://doi.org/https://doi.org/10.1287/msom.2019.0798
    Suppipat, S., & Hu, A. H. (2022). Achieving sustainable industrial ecosystems by design: A study of the ICT and electronics industry in Taiwan. Journal of Cleaner Production, 369, 133393. https://doi.org/10.1016/j.jclepro.2022.133393
    Tone, K., & Tsutsui, M. (2009). Network DEA: A slacks-based measure approach. Europeanjournalofoperationalresearch,197(1),243–252. https://doi.org/10.1016/j.ejor.2008.05.027
    Tone, K., & Tsutsui, M. (2010). Dynamic DEA: A slacks-based measure approach. Omega, 38(3-4), 145–156. https://doi.org/10.1016/j.omega.2009.07.003
    Wan, J., Li, X., Dai, H.-N., Kusiak, A., Martinez-Garcia, M., & Li, D. (2020). Artificial-intelligence-driven customized manufacturing factory: key technologies, applications, and challenges. Proceedings of the IEEE, 109(4), 377–398. https://doi.org/10.1109/JPROC.2020.3034808
    Xiang, W., Yu, K., Han, F., Fang, L., He, D., & Han, Q.-L. (2023). Advanced manufacturing in industry 5.0: A survey of key enabling technologies and future trends. IEEE Transactions on Industrial Informatics, 20(2), 1055–1068. https://doi.org/10.1109/TII.2023.3274224
    Yang, C.-H. (2022). How artificial intelligence technology affects productivity and employment: Firm-level evidence from Taiwan. Research Policy, 51(6), 104536. https://doi.org/https://doi.org/10.1016/j.respol.2022.104536

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