| 研究生: |
陳姿岑 Chen, Tzu-Tsen |
|---|---|
| 論文名稱: |
通信產業設備製造商與通信產業零組件供應商之DEA營運效率分析-以台灣為例 Operational Efficiency Analysis of Telecommunication Equipment Manufacturers and Telecommunication Component Suppliers in Taiwan: A DEA Approach |
| 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: | 69 |
| 中文關鍵詞: | 台灣通信產業 、分群比較 、製造端營運效率 、DEA SBM模型 |
| 外文關鍵詞: | Taiwan's Communications Industry, Group Comparison, Manufacturing Side Operational Efficiency, DEA SBM Model |
| 相關次數: | 點閱:73 下載:0 |
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近年來隨著 5G、物聯網與人工智慧等技術快速崛起,全球通信產業的競爭也越來越激烈,過去學術界對於台灣通信產業的效率研究相對有限,大多數文獻多聚焦於電信業者以及國外大廠作為研究對象,對於台灣通信產業公司進行系統性效率分析的研究為數不多。因此,本研究以20家台灣通信產業公司的營運效率進行量化分析,使用動態SBM模型(DEA-Dynamic SBM Model),再更進一步將這 20 家公司分為「通信產業設備製造商」與「通信產業零組件供應商」兩種類別,研究期間設定為 2020 年至 2024 年。設備製造商主要負責系統整合與終端設備生產,位於產業鏈的中下游,零組件供應商則提供射頻元件、天線模組、光通訊元件等核心技術產品,位於產業鏈的上游,本研究則採用資料包絡分析法DEA中的動態 SBM模型。
從實證結果來看,2022 年是整個研究期間效率表現最好的一年,這段時間正好對應到 COVID-19 疫情期間遠端工作及教學需求大幅增加,通信設備訂單大幅提升。然而,2024年整體效率出現明顯下滑,各公司之間的效率差距也隨之擴大,效率最低的公司與效率前緣之間的落差相當顯著,此一現象較可能是疫情帶動需求逐漸消退所致,而非企業本身經營出現問題。在分群比較方面,2020年至2024年零組件供應商的整體平均效率略高於設備製造商,這個結果反映出零組件供應商在技術導向的經營模式下,投入資源轉換為毛利產出的能力相對較好。本研究的分析結果顯示台灣通信產業製造端整體具備一定的營運效率基礎,但不同公司之間的資源配置能力仍存在相當落差。效率較好的公司通常能夠同時在人力、成本與研發等面向做到有效整合,並轉換出較佳的毛利表現,效率較弱的公司則多半在成本控制或研發尚有提升空間。
In recent years, the rapid development of technologies such as 5G, the Internet of Things, and artificial intelligence has driven increasingly intense competition within the global communications industry. Against this backdrop, this study examines the operational efficiency of 20 manufacturing side companies in Taiwan's communications industry between 2020 and 2024. The sample is divided into two groups communications equipment manufacturers and communications component suppliers. Equipment manufacturers are mainly engaged in system integration and end product manufacturing, whereas component suppliers focus on core technology products such as radio frequency (RF) components, antenna modules, and optical communication components. To evaluate efficiency across these two groups, the study applies the Dynamic SBM Model within Data Envelopment Analysis (DEA).
The empirical results show that 2022 marked the peak of efficiency performance over the study period, a pattern closely tied to the surge in demand for remote work and remote learning during the COVID-19 pandemic; efficiency then declined noticeably from 2024 onward. The findings also point to considerable gaps in resource allocation capability across companies. Firms with higher efficiency tend to integrate labor, cost, and R&D inputs more effectively, converting these advantages into stronger gross profit performance, while less efficient firms generally still have room to improve in cost control or R&D investment.
Banker, R. D., Charnes, A., & Cooper, W. W. (1984). Some models for estimating technical and scale inefficiencies in data envelopment analysis. Management science, 30(9), 1078–1092. https://doi.org/10.1287/mnsc.30.9.1078
Barczak, G. (1995). New product strategy, structure, process, and performance in the telecommunications industry. Journal of Product Innovation Management: an international publication of the product development & management association, 12(3), 224–234. https://doi.org/10.1111/1540-5885.1230224
Bourreau, M., & Doğan, P. (2001). Regulation and innovation in the telecommunications industry. Telecommunications Policy, 25(3), 167–184. https://doi.org/10.1016/S0308-5961(00)00087-2
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
Cheng, J. Z., Tsyu, J. Z., & Hsiao-Cheng, D. Y. (2003). Boom and gloom in the global telecommunications industry. Technology in Society, 25(1), 65–81. https://doi.org/10.1016/S0160-791X(02)00060-X
Cooper, W. W., Seiford, L. M., & Tone, K. (2007). Data envelopment analysis: a comprehensive text with models, applications, references and DEA-solver software (Vol. 2). Springer. https://doi.org/10.1007/b109347
Farrell, M. J. (1957). The measurement of productive efficiency. Journal of the royal statistical society series a: statistics in society, 120(3), 253–281. https://doi.org/10.2307/2343100
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/10.31803/tg-20210906103816
Hall, B. H., Mairesse, J., & Mohnen, P. (2010). Measuring the returns to R&D. In Handbook of the Economics of Innovation (Vol. 2, pp. 1033–1082). Elsevier. https://doi.org/10.1016/S0169-7218(10)02008-3
Hu, J.-L., & Wang, S.-C. (2006). Total-factor energy efficiency of regions in China. Energy policy, 34(17), 3206–3217. https://doi.org/10.1016/j.enpol.2005.06.015
Lera, E. (2000). Changing relations between manufacturing and service provision in a more competitive telecom environment. Telecommunications Policy, 24(5), 413–437. https://doi.org/10.1016/S0308-5961(00)00029-X
Li, F., & Whalley, J. (2002). Deconstruction of the telecommunications industry: from value chains to value networks. Telecommunications Policy, 26(9-10), 451–472. https://doi.org/10.1016/S0308-5961(02)00056-3
Lu, W.-M., & Hung, S.-W. (2010). Assessing the performance of a vertically disintegrated chain by the DEA approach–a case study of Taiwanese semiconductor firms. International Journal of Production Research, 48(4), 1155–1170. https://doi.org/10.1080/00207540802484929
McIvor, R. (2003). Outsourcing: insights from the telecommunications industry. Supply Chain Management: An International Journal, 8(4), 380–394. https://doi.org/10.1108/13598540310490134
Meena, M. E., & Geng, J. (2022). Dynamic competition in telecommunications: A systematic literature review. Sage Open, 12(2), 21582440221094609. https://doi.org/10.1177/21582440221094609
Miao, Y., Song, J., Lee, K., & Jin, C. (2018). Technological catch-up by east Asian firms: Trends, issues, and future research agenda. Asia Pacific Journal of Management, 35(3), 639–669. https://doi.org/10.1007/s10490-018-9566-z
Milana, C., & Zeli, A. (2002). The contribution of ICT to production efficiency in Italy: firm-level evidence using data envelopment analysis and econometric estimations. https://dx.doi.org/10.1787/101101136045
Reyes, P., Raisinghani, M. S., & Singh, M. (2002). Global supply chain management in the telecommunications industry: the role of information technology in integration of supply chain entities. Journal of Global Information Technology Management, 5(2), 48–67. https://doi.org/10.1080/1097198X.2002.10856325
Saharti, M. (2025). R&D and innovation and its impact on firm performance and market value: Panel evidence from G7 economies. Economies, 13(9), 254. https://doi.org/10.3390/economies13090254
Seol, S., Yoon, K., & Cho, D. (2024). Successful Technological Catch-Up Strategy: Empirical Evidence From Telecommunication Equipment Industry. Ieee Transactions on Engineering Management, 71, 11746–11757. https://doi.org/10.1109/tem.2024.3420172
Shin, N., Kraemer, K. L., & Dedrick, J. (2014). Value capture in global production networks: evidence from the Taiwanese electronics industry. Journal of the Asia Pacific Economy, 19(1), 74–88. https://doi.org/10.1080/13547860.2013.803844
Smith, P. (1990). Data envelopment analysis applied to financial statements. Omega, 18(2), 131–138. https://doi.org/10.1016/0305-0483(90)90060-M
Stiakakis, E., & Fouliras, P. (2009). The impact of environmental practices on firms’ efficiency: the case of ICT-producing sectors. Operational Research, 9(3), 311–328. https://doi.org/10.1007/s12351-009-0035-9
Stiakakis, E., & Sifaleras, A. (2013). Combining the priority rankings of DEA and AHP methodologies: a case study on an ICT industry. International Journal of Data Analysis Techniques and Strategies 7, 5(1), 101–114. https://doi.org/10.1504/IJDATS.2013.051743
Sturgeon, T. J., & Kawakami, M. (2011). Global value chains in the electronics industry: characteristics, crisis, and upgrading opportunities for firms from developing countries. International Journal of Technological Learning, Innovation and Development, 4(1-3), 120–147. https://doi.org/10.1504/IJTLID.2011.041902
Tone, K. (2001). A slacks-based measure of efficiency in data envelopment analysis. European journal of operational research, 130(3), 498–509. https://doi.org/10.1016/S0377-2217(99)00407-5
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
Tone, K., & Tsutsui, M. (2014). Dynamic DEA with network structure: A slacks-based measure approach. Omega, 42(1), 124–131. https://doi.org/10.1016/j.omega.2013.04.002
Tsai, K.-H. (2005). R&D productivity and firm size: a nonlinear examination. Technovation, 25(7), 795–803. https://doi.org/10.1016/j.technovation.2003.12.004
Yoseph Darius Purnama, R., Sri, R., & Khanlar Ilgar, G. (2024). 5G Technology’s Impact on Efficiency and Innovation in Telecommunications. Management Dynamics: International Journal of Management and Digital Sciences, 1(2), 10–19. https://doi.org/10.70062/managementdynamics.v1i2.445
Zhang, C., & Wang, X. (2019). The influence of ICT-driven innovation: a comparative study on national innovation efficiency between developed and emerging countries. Behaviour & Information Technology, 38(9), 876–886. https://doi.org/10.1080/0144929X.2019.1584645
Zhu, H., & Pasadilla, G. O. (2016). Manufacturing of telecommunications equipment. Services in Global Value Chains, 481–531. https://doi.org/10.1142/9789813141469_0015