簡易檢索 / 詳目顯示

研究生: 黃盈琇
Huang, Ying-Hsiu
論文名稱: 台灣光電產業營運、環境治理與市場效率之動態三階段分析—以RDM DDF Model 為例
Evaluating Operational, Environmental, and Market Efficiency in Taiwan's Optoelectronics Industry: Using a Dynamic Three-Stage RDM DDF Model
指導教授: 林泰宇
Lin, Tai-Yu
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: 2025
畢業學年度: 113
語文別: 中文
論文頁數: 81
中文關鍵詞: 光電產業營運效率環境效率市場效率DEA RDM DDF模型
外文關鍵詞: Optoelectronics industry, Operational efficiency , Environmental efficiency, Market efficiency, DEA RDM DDF model
相關次數: 點閱:31下載:2
分享至:
查詢本校圖書館目錄 查詢臺灣博碩士論文知識加值系統 勘誤回報
  • 隨著氣候變遷風險加劇與永續金融蓬勃發展,ESG已成為企業策略規劃與資本市場評價的重要基礎,其中環境構面因具高度系統性影響與轉型潛力,尤為關鍵。臺灣光電產業橫跨高科技與綠能應用兩大領域,不僅為能源轉型與碳中和政策的重要推動者,被政府列為六大核心戰略產業之一,同時亦為我國經濟發展之核心產業。然而,其製程高度依賴能源與水資源,伴隨潛在污染與環境風險,使得環境構面成為企業治理與政策管理的關鍵環節。近年來雖有學者應用資料包絡分析法(DEA)進行環境效率評估,但多集中於國家或區域層級,對於企業層級、特別是高科技製造產業中多元環境變數的整合分析仍付之闕如,顯示此一議題在學術與實務層面均有待深入探討。
    因此,本研究以台灣光電產業14家上市公司為樣本,選取2019至2023年五年期間資料,運用動態三階段RDM DDF模型(Three-Stage Dynamic RDM Directional Distance Function),從營運效率、環境治理效率與市場效率三個面向,全面評估企業表現。結果顯示,整體產業在三個階段的效率仍有顯著提升空間,尤其是市場階段,且企業間差異明顯,其中安集於三階段皆展現穩定且卓越的效率表現,可視為產業中的標竿企業。進一步分析七項環境相關變數發現,安集、富采、中環與凌巨等企業在五年間持續於各項環境變數上達成最佳效率,展現出高度一致且成熟的環境管理能力;其中,廢棄物排放效率為整體產業最容易達成之項目,顯示此類環境管理機制已普遍內化於企業日常營運流程中。此外,從技術導向分類進一步分析發現,光電整合導向企業於三階段效率中整體表現最為出色,本研究亦發現,企業在環境治理效率與財務績效之間的關聯,並非立即且線性發生,而是會因企業的技術導向與產業屬性而產生調節效果,此一現象顯示,環境治理成效對企業整體表現的影響,仍需依賴長期策略整合與制度成熟度,方能轉化為實質的營運與市場成果。

    This study investigates the environmental efficiency of Taiwan’s optoelectronics industry in response to escalating climate risks and the rising significance of ESG in corporate strategy and capital market evaluation. The industry plays a pivotal role in both high-tech innovation and green energy development but faces environmental challenges due to its resource-intensive production processes. Focusing on 14 listed companies from 2019 to 2023, this research employs the Three-Stage Dynamic RDM Directional Distance Function (DDF) model to assess firm performance from three dimensions: operational efficiency, environmental governance efficiency, and market efficiency. The findings reveal that, although improvements are needed across all stages, market efficiency shows the greatest lag. The firm ANJI consistently achieves superior performance across all three dimensions and is identified as a benchmark firm. In particular, ANJI, ENNOSTAR, CMC Magnetics, and GIANTPLUS exhibit strong and consistent environmental management, especially in waste treatment, which appears to be well-integrated into their routine operations. Furthermore, firms with integrated optoelectronic technology orientations tend to perform better across all efficiency dimensions. The study concludes that the link between environmental governance and financial performance is neither immediate nor linear but is moderated by firm-specific technological and structural factors. Hence, sustained strategic efforts and institutional maturity are crucial for translating environmental initiatives into measurable operational and market outcomes.

    摘要 i Abstract ii 誌謝 v 目錄 vi 表目錄 vii 圖目錄 viii 第一章 緒論 1 第一節 研究背景及動機 1 第二節 研究目的 3 第三節 研究架構 4 第二章 文獻回顧 6 第一節 環境構面在ESG中的角色與重要性 6 第二節 環境構面對企業財務影響 9 第三節 資料包絡分析法評估環境效率表現之文獻回顧 12 第三章 研究方法 18 第一節 資料包絡分析法的演進 18 第二節 方向距離函數 19 第三節 本文實證模型 20 第四章 實證結果與分析 23 第一節 資料來源、模型架構與變數說明 24 第二節 敘述統計分析 28 第三節 實證結果分析 31 第四節 四象限圖分析討論 53 第五節 分群討論 56 第五章 結論與建議 61 第一節 研究發現與結論 61 第二節 研究建議 64 第三節 研究限制與未來研究方向 66 參考文獻 67

    Afzalinejad, M. (2021). Evaluating radial efficiency considering environmental factors: A generalization of classical DEA. Measurement, 179, 109497.
    Agliardi, E., Alexopoulos, T., & Karvelas, K. (2023). The environmental pillar of ESG and financial performance: A portfolio analysis. Energy Economics, 120, 106598.
    Alizadeh, S., Vali, F., Vatani, Z., & Avami, A. (2023). Sustainable analysis of Waste-to-Energy systems in cities by eco-efficiency assessment using DEA approach: A case study of Iran's municipalities. Sustainable Cities and Society, 98, 104825.
    Alshehhi, J. M., & Zervopoulos, P. D. (2023). The effect of institutional factors on environmental efficiency: A cross-country analysis using a Bayesian data envelopment analysis approach. Journal of Cleaner Production, 395, 136401.
    An, Q., Cheng, Z., Shi, S., & Li, F. (2022). Environmental efficiency of Xiangjiang River in China: a data envelopment analysis cross-efficiency approach. Industrial Management & Data Systems, 122(2), 396-418.
    André, F. J., Buendía, A., & Santos-Arteaga, F. J. (2024). Efficient water use and reusing processes across Spanish regions: A circular data envelopment analysis with undesirable inputs. Journal of Cleaner Production, 434, 139929.
    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.
    Bashir, M. A., Qing, L., Razi, U., Xi, Z., & Jingting, L. (2025). A green leap forward: Environmental efficiency amidst natural resource and technological shifts. Renewable and Sustainable Energy Reviews, 216, 115686.
    Chambers, R. G., Chung, Y., & Färe, R. (1996). Benefit and distance functions. Journal of economic theory, 70(2), 407-419.
    Charnes, A., Cooper, W. W., & Rhodes, E. (1978). Measuring the efficiency of decision making units. European journal of operational research, 2(6), 429-444.
    Chen, P.-C., Yu, M.-M., Chang, C.-C., Hsu, S.-H., & Managi, S. (2015). The enhanced Russell-based directional distance measure with undesirable outputs: numerical example considering CO2 emissions. Omega, 53, 30-40.
    Chen, S.-L., Wang, D.-n., & Chen, H.-W. (2025). The impact of ESG factors on credit ratings: An empirical study of European banks. International Review of Economics & Finance, 104056.
    Cheng, L. T., Lee, S. K., Li, S. K., & Tsang, C. K. (2023). Understanding resource deployment efficiency for ESG and financial performance: A DEA approach. Research in International Business and Finance, 65, 101941.
    Cheng, X., & Feng, C. (2023). Does environmental information disclosure affect corporate cash flow? An analysis by taking media attentions into consideration. Journal of Environmental Management, 342, 118295.
    Chioatto, E., Fedele, A., Liscio, M. C., & Sospiro, P. (2024). Testing data envelopment analysis models on the performance of European Union regions in sustainable waste management. Waste management, 175, 170-182.
    Cortés-Borda, D., Polanco, J.-A., & Escobar-Sierra, M. (2024). Efficiency and Sustainability of the Hydropower Industry in Colombia: A Data Envelopment Analysis of Stakeholders’ Perceptions. Journal of Water Resources Planning and Management, 150(12), 04024057.
    Dallocchio, M., Pistolesi, F., & Teti, E. (2025). Conciliating environmental and financial performance in emerging countries. Finance Research Letters, 74, 106781.
    das Mercês Costa, I., Dias, M. F., & Robaina, M. (2024). Evaluation of the efficiency of urban solid waste management in Brazil by data envelopment analysis and possible variables of influence. Waste Disposal & Sustainable Energy, 6(2), 283-295.
    de la Fuente, G., & Velasco, P. (2024). Pretending to be sustainable: Is ESG disparity a symptom? Journal of Contemporary Accounting & Economics, 20(2), 100418.
    Delgado-Antequera, L., Gémar, G., Molinos-Senante, M., Gómez, T., Caballero, R., & Sala-Garrido, R. (2021). Eco-efficiency assessment of municipal solid waste services: Influence of exogenous variables. Waste management, 130, 136-146.
    Díaz, V., Ibrushi, D., & Zhao, J. (2021). Reconsidering systematic factors during the COVID-19 pandemic–The rising importance of ESG. Finance Research Letters, 38, 101870.
    Färe, R., & Grosskopf, S. (2010). Directional distance functions and slacks-based measures of efficiency. European journal of operational research, 200(1), 320-322.
    Farrell, M. J. (1957). The measurement of productive efficiency. Journal of the royal statistical society series a: statistics in society, 120(3), 253-281.
    Fathi, B., Ashena, M., & Bahari, A. R. (2021). Energy, environmental, and economic efficiency in fossil fuel exporting countries: A modified data envelopment analysis approach. Sustainable Production and Consumption, 26, 588-596.
    Gül, Y., & Altuntaş, C. (2024). Do ESG Ratings Affect Stock Prices? The Case of Developed and Emerging Stock Markets. Sosyoekonomi, 32(60), 243-258.
    Gyönyör, L. S., & Horváth, M. (2024). Does ESG affect stock market dependence? An empirical exploration of S&P 1200 companies shows the divergent nature of E–S–G pillars. Research in International Business and Finance, 69, 102230.
    Halkos, G., de Alba, J. M., & Bampatsou, C. (2024). Determinants of environmental efficiency and sources of productivity change in the manufacturing sector: A comparative analysis between Europe and Asia. Energy, 291, 130355.
    Hu, J.-L., & Wang, S.-C. (2006). Total-factor energy efficiency of regions in China. Energy policy, 34(17), 3206-3217.
    Jin, Y. (2025). Distinctive impacts of esg pillars on corporate financial performance: A random forest analysis of korean listed firms. Finance Research Letters, 71, 106395.
    Li, X. N., Feng, Y., Chiu, Y. H., Lin, T. Y., & Chiu, S. Y. (2021). Recycling water and sludge disposal efficiency in China's sewage treatment industry. Managerial and Decision Economics, 42(7), 1703-1717.
    Lin, R., & Li, Z. (2023). Intertemporal environmental efficiency assessment in China: A new network-based dynamic super-efficiency measure. Plos one, 18(8), e0290896.
    Lin, T.-Y., Chiu, Y.-h., Chen, C.-H., & Ji, L. (2025). Renewable energy consumption efficiency, greenhouse gas emission efficiency, and climate change in Europe. Geoenergy Science and Engineering, 247, 213665.
    Lin, T.-Y., Chiu, Y.-H., Lin, Y.-N., & Chang, T.-H. (2023). Profit-seeking enterprise production and business waste treatment efficiency in Taiwan. Environment, Development and Sustainability, 25(10), 10661-10683.
    lo Storto, C. (2024). Measuring the eco-efficiency of municipal solid waste service: A fuzzy DEA model for handling missing data. Utilities Policy, 86, 101706.
    Lu, W. M., Kuo, K. C., Kweh, Q. L., & Ganbaatar, O. (2025). Environmental, social, and governance, board gender diversity, and firm efficiency: Evidence from the global mining industry pre‐and post‐COVID‐19 pandemic. Corporate Social Responsibility and Environmental Management, 32(1), 1002-1023.
    Mamghaderi, M., Mamkhezri, J., & Khezri, M. (2023). Assessing the environmental efficiency of OECD countries through the lens of ecological footprint indices. Journal of Environmental Management, 338, 117796.
    Mashayekhi, B., Asiaei, K., Rezaee, Z., Jahangard, A., Samavat, M., & Homayoun, S. (2024). The relative importance of ESG pillars: A two‐step machine learning and analytical framework. Sustainable Development, 32(5), 5404-5420.
    Matsumoto, K. i., Makridou, G., & Doumpos, M. (2020). Evaluating environmental performance using data envelopment analysis: The case of European countries. Journal of Cleaner Production, 272, 122637.
    Óskarsson, G. K., Agnarsson, S., & Davíðsdóttir, B. (2025). Evaluating municipal solid waste management efficiency in Iceland: A data envelopment analysis of socioeconomic and geographic influences. Environmental and Sustainability Indicators, 26, 100676.
    Portela, M. S., Thanassoulis, E., & Simpson, G. (2004). Negative data in DEA: A directional distance approach applied to bank branches. Journal of the operational research society, 55(10), 1111-1121.
    Sala-Garrido, R., Mocholi-Arce, M., Maziotis, A., & Molinos-Senante, M. (2024). Energy efficiency evaluation of wastewater treatment plants: A methodological proposal for its benchmarking. Environmental Science & Policy, 162, 103915.
    Senadheera, S. S., Withana, P. A., Dissanayake, P. D., Sarkar, B., Chopra, S. S., Rhee, J. H., & Ok, Y. S. (2021). Scoring environment pillar in environmental, social, and governance (ESG) assessment. Sustainable Environment, 7(1), 1960097.
    Tone, K. (2001). A slacks-based measure of efficiency in data envelopment analysis. European journal of operational research, 130(3), 498-509.
    Tone, K., & Tsutsui, M. (2014). Dynamic DEA with network structure: A slacks-based measure approach. Omega, 42(1), 124-131.
    Trahan, R. T., & Jantz, B. (2023). What is ESG? Rethinking the “E” pillar. Business strategy and the environment, 32(7), 4382-4391.
    Truant, E., Borlatto, E., Crocco, E., & Bhatia, M. (2023). ESG performance and technological change: Current state-of-the-art, development and future directions. Journal of Cleaner Production, 429, 139493.
    Yusifzada, L., Lončarski, I., Czupy, G., & Naffa, H. (2025). Return trade-offs between environmental and social pillars of ESG scores. Research in International Business and Finance, 102779.
    Zanin, L. (2022). Estimating the effects of ESG scores on corporate credit ratings using multivariate ordinal logit regression. Empirical Economics, 62(6), 3087-3118.
    Zhu, Y., Yang, F., Wei, F., & Wang, D. (2022). Measuring environmental efficiency of the EU based on a DEA approach with fixed cost allocation under different decision goals. Expert Systems with Applications, 208, 118183.

    下載圖示 校內:立即公開
    校外:立即公開
    QR CODE