簡易檢索 / 詳目顯示

研究生: 吳志昭
Wu, Chih-Chao
論文名稱: 影響手機電子廠商使用RoHS的製程材料關鍵要素分析
A Derivation of Key Success Factors for Influencing the Adoption of RoHS Process Materials by Mobile Phone Manufacturers
指導教授: 郭金國
Kuo, Chin-Guo
學位類別: 碩士
Master
系所名稱: 工業教育學系
Department of Industrial Education
論文出版年: 2018
畢業學年度: 106
語文別: 英文
論文頁數: 42
中文關鍵詞: RoHS製程材料影響因素綠色製造TOE模式
英文關鍵詞: RoHS, Process material, Influencing factors, Green manufacturing, TOE
DOI URL: http://doi.org/10.6345/THE.NTNU.DIE.047.2018.E01
論文種類: 學術論文
相關次數: 點閱:123下載:14
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
  • 隨著全球暖化日趨嚴重,以及消費者對環境保護與綠色消費意識的日漸重視,因此,在全球環保意識的提升、綠色技術的持續發展以及各國對環境保護的重視與要求,產品的生產製造,必須兼具環保;本研究將導入技術背景、組織背景及外在環境背景(Technological context, Organizational context and Environmental context, TOE) 模式,針對我國手機廠商使用「危害物質禁用指令」(RoHS;Restriction of the use of certain hazardous substance in elec-trical and electronic equipment)的製程材料關鍵要素進行分析,並探討如何導入適當的技術策略,以提升企業的競爭力。本研究將以偏最小平方結構方程模型(Partial Least Squares Structural Equation Modeling, PLS-SEM)檢定TOE模式之假設顯著,並以本國手機製造廠商之專業經理人為樣本,實證本研究架構之可行性。實證研究的結果,將可作為政府單位訂定倡導科技業導入RoHS製程材料環保政策之用。

    關鍵字:RoHS、製程材料、影響因素、綠色製造、TOE模式

    The global warming is increasingly serious, as well as consumer envi-ronmental protection and green consumer awareness of the awakening, there-fore, in the global awareness of environmental protection, green technology, sustainable development and national environmental protection and the re-quirements of the product in the manufacturing requirements, must meet the technical and environmental protection of the production environment; this study explores the adoption of Restriction of the use of certain hazardous substance in electrical and electronic equipment (RoHS) in terms of Taiwan's mobile electronics manufacturers for understanding the adopting behaviors of firms to use the "Hazardous Substances Directive", and further analyzes the key factors of the process material under the RoHS directive and how to use the appropriate technical strategy to enhance the competitiveness of the en-terprise through the previous target specification. In this study, the PLS-SEM method will be utilized to confirm the hypothesized relationships based on TOE model. The proposed model and empirical results can serve as the basis to define the environmental protection policy to promote the RoHS materials.

    Keywords: RoHS, Process material, Influencing factors, Green
    manufacturing, TOE

    摘要 i Abstract ii Table of Contents iii List of Table v List of Figure vi Chapter 1 Introduction 1 1.1 Research Backgrounds and Motivations 1 1.2 Research Purposes 3 1.3 Research Scope 3 1.4 Research Limitations 4 1.5 Research Process 5 Chapter 2 Literature review 7 2.1 Sustainability 7 2.2 Green Manufacturing 8 2.3 The TOE Framework 10 2.3.1 Technological Background (TB) 10 2.3.2 Organizational Background (OB) 12 2.3.3 Environmental Background (EB) 13 2.4 Factors Influencing the Adoption of Green Process Materials 14 Chapter 3 Research Method 17 3.1 Partial Least Squares based Structural Equation Model (PLS-SEM) 17 Chapter 4 Empirical Study 21 4.1 Data Collection and Analysis 21 4.2 Descriptive Statistics 22 4.3 Measurement Model Assessment 23 4.4 Structural Model Assessment 25 Chapter 5 Discussion 29 Chapter 6 Conclusion 33 References 35 Appendix 41

    Aboelmaged, M. (2018). The drivers of sustainable manufacturing practices in Egyptian SMEs and their impact on competitive capabilities: A PLS-SEM model. Journal of Cleaner Production, 175, 207-221.

    Ahani, A., Rahim, N. Z. A., & Nilashi, M. (2017). Forecasting social CRM adoption in SMEs: A combined SEM-neural network method. Computers in Human Behavior, 75, 560-578.

    Ben-Eli, M. (2004). Sustainability: The Five Core Principles–A New Framework. New York, USA: Buckminster Fuller Institute.

    Ben-Eli, M. (2006). Sustainability: The five core principles. New York, USA: Sustainbility Laboratory.

    Brewer, B., & Arnette, A. N. (2017). Design for procurement: What procurement driven design initiatives result in environmental and economic performance improvement? Journal of Purchasing and Supply Management, 23(1), 28-39.

    Carter, C. R., & Rogers, D. S. (2008). A framework of sustainable supply chain management: moving toward new theory. International journal of physical distribution & logistics management, 38(5), 360-387.

    Chin, W. W. (1998). The partial least squares approach to structural equation modeling. Modern methods for business research, 295(2), 295-336.

    Chong, A. Y.-L., & Chan, F. T. (2012). Structural equation modeling for multi-stage analysis on Radio Frequency Identification (RFID) diffusion in the health care industry. Expert Systems with Applications, 39(10), 8645-8654.

    Co-operation, O. f. E., & ., D. (2009). Eco-innovation in industry: enabling green growth: OECD.

    Cousins, P. D., Lamming, R. C., & Bowen, F. (2004). The role of risk in environment-related supplier initiatives. International journal of operations & production Management, 24(6), 554-565.

    Dyball, R., Brown, V. A., & Keen, M. (2007). Towards sustainability: Five strands of social learning. Social learning towards a sustainable world, 181-194.

    Fornell, C., & Larcker, D. F. (1981). Evaluating structural equation models with unobservable variables and measurement error. Journal of Marketing Research, 39-50.

    Fornell, C., & Bookstein, F. L. (1982). Two structural equation models: LISREL and PLS applied to consumer exit-voice theory. Journal of Marketing research, 440-452.

    Ghobakhloo, M., Hong, T. S., Sabouri, M. S., & Zulkifli, N. (2012). Strategies for successful information technology adoption in small and medium-sized enterprises. Information, 3(1), 36-67.
    Götz, O., Liehr-Gobbers, K., & Krafft, M. (2010). Evaluation of structural equation models using the partial least squares (PLS). Berlin, Heidelberg : Springer.

    Hair Jr, J. F., Hult, G. T. M., Ringle, C., & Sarstedt, M. (2016). A primer on partial least squares structural equation modeling (PLS-SEM). New York, USA: Sage Publications.

    Henseler, J., Ringle, C. M., & Sarstedt, M. (2012). Using partial least squares path modeling in advertising research: basic concepts and recent issues. London, England: Edward Elgar Publishing

    Henseler, J., Ringle, C. M., & Sinkovics, R. R. (2009). The use of partial least squares path modeling in international marketing. London, England: Emerald Group Publishing Limited.

    Hsu, C.-C., Choon Tan, K., Hanim Mohamad Zailani, S., & Jayaraman, V. (2013). Supply chain drivers that foster the development of green initiatives in an emerging economy. International journal of operations & production Management, 33(6), 656-688.

    Jia, Q., Guo, Y., & Barnes, S. J. (2017). Enterprise 2.0 post-adoption: Extending the information system continuance model based on the technology-Organization-environment framework. Computers in Human Behavior, 67, 95-105.

    Lin, S.-H. (2011). Applying Particle Swarm Optimization Algorithm to Material Selection and Manufacturing Production Planning in Green Design. MA. Thesis. Yuan Ze University Department of Industrial Engineering and Management, 1-117.

    Lippert, S. K., & Govindarajulu, C. (2006). Technological, organizational, and environmental antecedents to web services adoption. Communications of the IIMA, 6(1), 14.

    Melnyk, S., Sroufe, R., Montabon, F., & Hinds, T. (2001). Green MRP: identifying the material and environmental impacts of production schedules. International Journal of Production Research, 39(8), 1559-1573.

    Nunnally, J. C. (2010). Psychometric Theory 3E. New York, USA: Tata McGraw-Hill Education.

    Oliveira, T., & Martins, M. F. (2011). Literature review of information technology adoption models at firm level. Electronic Journal of Information Systems Evaluation, 14(1), 110.

    Oliveira, T., Thomas, M., & Espadanal, M. (2014). Assessing the determinants of cloud computing adoption: An analysis of the manufacturing and services sectors. Information & Management, 51(5), 497-510.

    Ooi, K.-B., Lee, V.-H., Tan, G. W.-H., Hew, T.-S., & Hew, J.-J. (2018). Cloud computing in manufacturing: The next industrial revolution in Malaysia? Expert Systems with Applications, 93, 376-394.

    Scallon, M., & Sten, M. (1996). Environmental Positioning for the Future: A Review of 36 Leading Companies in the Pacific Northwest Region of the United States of America. Greener Management International, 49-65.

    SIMPEH, E. K. (2015). Factors Influencing the Growth of Green Building in the South African Construction Industry. Smart and Sustainable Built Environment (SASBE) Conference 2015. 303-310

    Tajudeen, F. P., Jaafar, N. I., & Ainin, S. (2018). Understanding the impact of social media usage among organizations. Information & Management, 55(3), 308-321.

    Tornatzky, L. G., Fleischer, M., & Chakrabarti, A. (1990). Processes of technological innovation (Issues in organization and management series). Lanham, USA: Lexington Books

    Trinchera, L. (2008). Unobserved Heterogeneity in Structural Equation Models: a new approach to latent class detection in PLS Path Modeling. Napoli, Italy: Università degli Studi di Napoli Federico II.

    Tushman, M., & Nadler, D. (1986). Organizing for innovation. California management review, 28(3), 74-92.
    Vachon, S., & Klassen, R. D. (2006). Extending green practices across the supply chain: the impact of upstream and downstream integration. International journal of operations & production Management, 26(7), 795-821.

    Wang, Z. Z. (2001). The Use of Material and Continuable Development. Machine Design and Manufacturing Engineering, 30(3), 9-10.

    Weng, H.-H. R., Chen, J.-S., & Chen, P.-C. (2015). Effects of green innovation on environmental and corporate performance: A stakeholder perspective. Sustainability, 7(5), 4997-5026.

    Xu, W., Ou, P., & Fan, W. (2017). Antecedents of ERP assimilation and its impact on ERP value: A TOE-based model and empirical test. Information Systems Frontiers, 19(1), 13-30.

    Yee-Loong Chong, A., & Ooi, K.-B. (2008). Adoption of interorganizational system standards in supply chains: an empirical analysis of RosettaNet standards. Industrial Management & Data Systems, 108(4), 529-547.

    下載圖示
    QR CODE