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題名 以TOE架構探討影響企業採行工業4.0意圖之因素
Factors influencing the intention of industry 4.0 adoption: A TOE framework perspective
作者 黃駿祐
Huang, Chun-Yu
貢獻者 羅明琇
黃駿祐
Huang, Chun-Yu
關鍵詞 工業4.0
TOE架構
新科技採行
意圖
Industry 4.0
TOE framework
New technology adopting
Intention
日期 2018
上傳時間 2-Aug-2018 16:43:46 (UTC+8)
摘要 近年隨著全球消費市場以及生產要素條件的變化，傳統製造模式開始面臨諸多挑戰，此時，結合大數據、演算法以及新興科技的「工業4.0」便作為解決方案被德國提出，眾多企業開始投入相關的應用，類似的概念也陸續成為各國政府的政策方向。然而，導入新的製造模式會對企業產生極大的負擔，在具備適當的條件與足夠的動機前，企業並不會貿然導入，這使得工業4.0在業界的實行程度仍然不高。因此，本研究以不同規模及來自不同產業但皆具備採行工業4.0意圖之企業為研究標的，深入探討影響其採行意圖之因素，並發掘背後共同條件以及關鍵推力與阻力。
     
     本研究以科技－組織－環境架構（Technology-Organization-Environment Framework, TOE Framework）作為分析架構，探討新技術特性以及企業內外部條件因素對採行意圖之影響，並對四家公司進行個案研究，驗證其中的關鍵影響因素。
     
     本研究發現，儘管四間公司的產業、規模以及自動化程度皆不盡相同，科技面因素對企業採行意圖皆造成很大的影響，企業對於工業4.0應用本身的成本效益評估是主要的意圖來源；而內部組織面則是共同具備執行能力、財務資源以及對新技術態度正向的領導者；環境因素會受公司背景與產業環境而有較大差異，但客戶面的產業準備程度對企業採行意圖與方式皆有很大的影響。阻力與挑戰方面，成本效益不易評估是四間公司導入時的共同阻礙；缺少執行能力、相關知識人才對規模較小的傳統產業形成挑戰；而無法找到適合的工業4.0方案則是傳統產業所面臨的問題。
     
     本研究對學術上的貢獻是以TOE架構探討過去較少被討論之工業4.0採行意圖之議題，並發現相對優勢、科技準備程度、執行能力、領導者特質與財務資源是影響工業4.0採行意圖的關鍵因素。在實務上的貢獻，則提供自身欲導入工業4.0，或欲推行工業4.0之政府機構以及技術供應商作為參考。
In recent years, the traditional manufacturing method has been challenged with the changes in the consumer market and the factors of production. The concept of Industry 4.0, a new manufacturing method which is correlated with big data, algorithms and high technologies, was proposed as a solution by the German government and has become a trend. However, it is difficult for many companies to implement Industry 4.0-related practices without appropriate conditions and strong driving forces due to huge implementing cost. In the light of this, this study targets the companies from different background, which have strong intention of adopting Industry 4.0, aiming to explore what and how the factors influence their intention.
     
     This study uses the Technology-Organization-Environment Framework (TOE Framework) as an analytical framework to explore the impact of the characteristics of the new technology and the internal and external conditions of the enterprise. The case study approach is selected for the research methods and four companies are analyzed.
     
     The result of this study indicates that the technical factors strongly influence a firm’s intention of adopting Industry 4.0. The cost-benefit evaluation of new technology is the main source of intention. For organizational factors, a firm ’s capacity, financial resources, and leader’s positive attitude are the common conditions for four companies. In terms of environmental factors, the result is greatly different by the firm’s background, but the industrial preparation is an important factor for each firm. The result also points out that cost-benefit evaluation, lack of capacity, and no suitable solution provider are the resistances and challenges of adopting Industry 4.0.
     
     The study contributes to the literature of Industry 4.0 by utilizing the TOE framework for exploring the key influencing factors of Industry 4.0 intention. It also provides a guideline to governments and solution providers for promoting the solution of Industry 4.0.
參考文獻 英文部分
     1. Aboelmaged, M. G. (2014). Predicting e-readiness at firm-level: An analysis of technological, organizational and environmental (TOE) effects on e-maintenance readiness in manufacturing firms. International Journal of Information Management, 34(5), 639-651.
     2. Dilberoglu, U. M., Gharehpapagh, B., Yaman, U., & Dolen, M. (2017). The role of additive manufacturing in the era of industry 4.0. Procedia Manufacturing, 11, 545-554.
     3. Gartner (2016). Gartner’s Top 10 Strategic Technology Trends for 2017. https://www.gartner.com/smarterwithgartner/gartners-top-10-technology-trends-2017/
     4. Ghobakhloo, M., Arias-Aranda, D., & Benitez-Amado, J. (2011). Adoption of e-commerce applications in SMEs. Industrial Management & Data Systems, 111(8), 1238-1269.
     5. Giusto, D., Iera, A., Morabito, G., & Atzori, L. (Eds.). (2010). The internet of things: 20th Tyrrhenian workshop on digital communications. Springer Science & Business Media.
     6. Gutierrez, A., Boukrami, E., & Lumsden, R. (2015). Technological, organisational and environmental factors influencing managers’ decision to adopt cloud computing in the UK. Journal of Enterprise Information Management, 28(6), 788-807.
     7. Hermann, M., Pentek, T., & Otto, B. (2016, January). Design principles for industrie 4.0 scenarios. In System Sciences (HICSS), 2016 49th Hawaii International Conference on (pp. 3928-3937). IEEE.
     8. Kagermann, H., Helbig, J., Hellinger, A., & Wahlster, W. (2013). Recommendations for implementing the strategic initiative INDUSTRIE 4.0: Securing the future of German manufacturing industry; final report of the Industrie 4.0 Working Group. Forschungsunion.
     9. Kuan, K. K., & Chau, P. Y. (2001). A perception-based model for EDI adoption in small businesses using a technology–organization–environment framework. Information & management, 38(8), 507-521.
     10. Kumar, K. N., Chandra, S., Bharati, S., & Manava, S. (2016, June). Factors Influencing Adoption of Augmented Reality Technology for E-Commerce. In PACIS (p. 342).
     11. Lasi, H., Fettke, P., Kemper, H. G., Feld, T., & Hoffmann, M. (2014). Industry 4.0. Business & Information Systems Engineering, 6(4), 239-242.
     12. Lee, E. A. (2008, May). Cyber physical systems: Design challenges. In 11th IEEE Symposium on Object Oriented Real-Time Distributed Computing (ISORC) (pp. 363-369). IEEE.
     13. Nunes, M. L., Pereira, A. C., & Alves, A. C. (2017). Smart products development approaches for Industry 4.0. Procedia Manufacturing, 13, 1215-1222.
     14. Lu, Y. (2017). Industry 4.0: A survey on technologies, applications and open research issues. Journal of Industrial Information Integration, 6, 1-10.
     15. Lucke, D., Constantinescu, C., & Westkämper, E. (2008). Smart factory-a step towards the next generation of manufacturing. In Manufacturing systems and technologies for the new frontier (pp. 115-118). Springer, London.
     16. McKinsey. (2016). Industry 4.0 after the initial hype- Where manufacturers are finding value and how they can best capture it. McKinsey Digital 2016. https://www.mckinsey.com/business-functions/operations/our-insights/industry-40-looking-beyond-the-initial-hype
     17. 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.
     18. Paelke, V. (2014, September). Augmented reality in the smart factory: Supporting workers in an industry 4.0. environment. In Emerging Technology and Factory Automation (ETFA), 2014 IEEE (pp. 1-4). IEEE.
     19. Palacios-Marqués, D., Soto-Acosta, P., & Merigó, J. M. (2015). Analyzing the effects of technological, organizational and competition factors on Web knowledge exchange in SMEs. Telematics and Informatics, 32(1), 23-32.
     20. Pan, M. J., & Jang, W. Y. (2008). Determinants of the adoption of enterprise resource planning within the technology-organization-environment framework: Taiwan`s communications industry. Journal of Computer information systems, 48(3), 94-102.
     21. Picoto, W. N., Bélanger, F., & Palma-dos-Reis, A. (2014). A technology–organisation–environment (TOE)-based m-business value instrument. International Journal of Mobile Communications, 12(1), 78-101.
     22. Porter, M. E., & Heppelmann, J. E. (2015). How smart, connected products are transforming companies. Harvard Business Review, 93(10), 96-114.
     23. Puklavec, B., Oliveira, T., & Popovič, A. (2014). Unpacking business intelligence systems adoption determinants: An exploratory study of small and medium enterprises. Economic and Business Review, 16(2), 185-213.
     24. PwC. (2018). Global Digital Operations Study 2018 Digital Champions- How industry leaders build integrated operations ecosystems to deliver end-to-end customer solutions. Global Digital Operations 2018 Survey. https://www.strategyand.pwc.com/media/file/Global-Digital-Operations-Study_Digital-Champions.pdf
     25. Seethamraju, R. (2015). Adoption of software as a service (SaaS) enterprise resource planning (ERP) systems in small and medium sized enterprises (SMEs). Information systems frontiers, 17(3), 475-492.
     26. Stock, T., & Seliger, G. (2016). Opportunities of sustainable manufacturing in industry 4.0. Procedia Cirp, 40, 536-541.
     27. Sun, S., Cegielski, C. G., Jia, L., & Hall, D. J. (2018). Understanding the Factors Affecting the Organizational Adoption of Big Data. Journal of Computer Information Systems, 58(3), 193-203.
     28. Tehrani, S. R., & Shirazi, F. (2014, June). Factors influencing the adoption of cloud computing by small and medium size enterprises (SMEs). In International Conference on Human Interface and the Management of Information (pp. 631-642). Springer, Cham.
     29. Tornatzky, L.G. & Fleischer, M. (1990). The Process of Technological Innovation. Lexington, MA: Lexington Books.
     30. Wei, J., Lowry, P. B., & Seedorf, S. (2015). The assimilation of RFID technology by Chinese companies: a technology diffusion perspective. Information & Management, 52(6), 628-642.
     31. Xu, X. (2012). From cloud computing to cloud manufacturing. Robotics and computer-integrated manufacturing, 28(1), 75-86.
     32. Yeboah-Boateng, E. O., & Essandoh, K. A. (2014). Factors influencing the adoption of cloud computing by small and medium enterprises in developing economies. International Journal of Emerging Science and Engineering, 2(4), 13-20.
     33. Yeh, C. C., & Chen, Y. F. (2018). Critical success factors for adoption of 3D printing. Technological Forecasting and Social Change, 132, 209-216.
     34. Yin, R. K. (1994). Case Study Research: Design and Methods (Applied Social Research Methods, Vol. 5). Sage Publications, Beverly Hills, CA. Rick Rantz Leading urban institutions of higher education in the new millennium Leadership & Organization Development Journal, 23(8), 2002.
     35. Yoon, T. E., & George, J. F. (2013). Why aren’t organizations adopting virtual worlds?. Computers in Human Behavior, 29(3), 772-790.
     36. Zhu, K., Kraemer, K., & Xu, S. (2003). Electronic business adoption by European firms: a cross-country assessment of the facilitators and inhibitors. European Journal of Information Systems, 12(4), 251-268.
     
     中文部分
     1. 王怡惠（2015）。從工業4.0 看我國生產力4.0的挑戰。臺灣經濟研究月刊38卷8期。
     2. 李傑、倪軍、王安正（2017）。《從大數據到智慧生產與服務創新》，新北市：前程文化。
     3. 李傑（2016）。《工業大數據 工業4.0時代的智慧轉型與價值創新》，台北市：天下雜誌。
     4. 汪建南、馬雲龍 (2016) 。工業4.0 的國際發展趨勢與臺灣因應之道。國際金融參考資料第六十九輯。
     5. 林淑馨（2010）。《質性研究：理論與實務》，巨流。
     6. 韋康博（2015）。《工業4.0 從製造業到「智」造業，下一波產業革命如何顛覆全世界？》，台北市：商周。
     7. 邦亭 (2016)。獨家專訪德國工業4.0平台秘書長邦廷：企業不改變，就等著關門大吉，天下雜誌，601期：頁90-93
描述 碩士
國立政治大學
企業管理研究所(MBA學位學程)
105363112
資料來源 http://thesis.lib.nccu.edu.tw/record/#G0105363112
資料類型 thesis
dc.contributor.advisor 羅明琇zh_TW
dc.contributor.author (Authors) 黃駿祐zh_TW
dc.contributor.author (Authors) Huang, Chun-Yuen_US
dc.creator (作者) 黃駿祐zh_TW
dc.creator (作者) Huang, Chun-Yuen_US
dc.date (日期) 2018en_US
dc.date.accessioned 2-Aug-2018 16:43:46 (UTC+8)-
dc.date.available 2-Aug-2018 16:43:46 (UTC+8)-
dc.date.issued (上傳時間) 2-Aug-2018 16:43:46 (UTC+8)-
dc.identifier (Other Identifiers) G0105363112en_US
dc.identifier.uri (URI) http://nccur.lib.nccu.edu.tw/handle/140.119/119177-
dc.description (描述) 碩士zh_TW
dc.description (描述) 國立政治大學zh_TW
dc.description (描述) 企業管理研究所(MBA學位學程)zh_TW
dc.description (描述) 105363112zh_TW
dc.description.abstract (摘要) 近年隨著全球消費市場以及生產要素條件的變化，傳統製造模式開始面臨諸多挑戰，此時，結合大數據、演算法以及新興科技的「工業4.0」便作為解決方案被德國提出，眾多企業開始投入相關的應用，類似的概念也陸續成為各國政府的政策方向。然而，導入新的製造模式會對企業產生極大的負擔，在具備適當的條件與足夠的動機前，企業並不會貿然導入，這使得工業4.0在業界的實行程度仍然不高。因此，本研究以不同規模及來自不同產業但皆具備採行工業4.0意圖之企業為研究標的，深入探討影響其採行意圖之因素，並發掘背後共同條件以及關鍵推力與阻力。
     
     本研究以科技－組織－環境架構（Technology-Organization-Environment Framework, TOE Framework）作為分析架構，探討新技術特性以及企業內外部條件因素對採行意圖之影響，並對四家公司進行個案研究，驗證其中的關鍵影響因素。
     
     本研究發現，儘管四間公司的產業、規模以及自動化程度皆不盡相同，科技面因素對企業採行意圖皆造成很大的影響，企業對於工業4.0應用本身的成本效益評估是主要的意圖來源；而內部組織面則是共同具備執行能力、財務資源以及對新技術態度正向的領導者；環境因素會受公司背景與產業環境而有較大差異，但客戶面的產業準備程度對企業採行意圖與方式皆有很大的影響。阻力與挑戰方面，成本效益不易評估是四間公司導入時的共同阻礙；缺少執行能力、相關知識人才對規模較小的傳統產業形成挑戰；而無法找到適合的工業4.0方案則是傳統產業所面臨的問題。
     
     本研究對學術上的貢獻是以TOE架構探討過去較少被討論之工業4.0採行意圖之議題，並發現相對優勢、科技準備程度、執行能力、領導者特質與財務資源是影響工業4.0採行意圖的關鍵因素。在實務上的貢獻，則提供自身欲導入工業4.0，或欲推行工業4.0之政府機構以及技術供應商作為參考。		zh_TW
dc.description.abstract (摘要) In recent years, the traditional manufacturing method has been challenged with the changes in the consumer market and the factors of production. The concept of Industry 4.0, a new manufacturing method which is correlated with big data, algorithms and high technologies, was proposed as a solution by the German government and has become a trend. However, it is difficult for many companies to implement Industry 4.0-related practices without appropriate conditions and strong driving forces due to huge implementing cost. In the light of this, this study targets the companies from different background, which have strong intention of adopting Industry 4.0, aiming to explore what and how the factors influence their intention.
     
     This study uses the Technology-Organization-Environment Framework (TOE Framework) as an analytical framework to explore the impact of the characteristics of the new technology and the internal and external conditions of the enterprise. The case study approach is selected for the research methods and four companies are analyzed.
     
     The result of this study indicates that the technical factors strongly influence a firm’s intention of adopting Industry 4.0. The cost-benefit evaluation of new technology is the main source of intention. For organizational factors, a firm ’s capacity, financial resources, and leader’s positive attitude are the common conditions for four companies. In terms of environmental factors, the result is greatly different by the firm’s background, but the industrial preparation is an important factor for each firm. The result also points out that cost-benefit evaluation, lack of capacity, and no suitable solution provider are the resistances and challenges of adopting Industry 4.0.
     
     The study contributes to the literature of Industry 4.0 by utilizing the TOE framework for exploring the key influencing factors of Industry 4.0 intention. It also provides a guideline to governments and solution providers for promoting the solution of Industry 4.0.		en_US
dc.description.tableofcontents 摘要 i
     英文摘要 ii
     目錄 iii
     圖表目錄 iv
     第一章 緒論 1
     1.1 研究背景與動機 1
     1.2 研究目的 2
     1.3 研究內容 2
     1.4 研究流程 3
     第二章 文獻探討 4
     2.1 工業4.0（Industry 4.0） 4
     2.2 科技－組織－環境架構（TOE Framework） 7
     第三章 研究方法 14
     3.1 研究方法 14
     3.2 研究對象 15
     3.3 個案分析架構 16
     第四章 個案分析 19
     4.1 A塑膠射出成型廠 19
     4.2 B不鏽鋼表面處理廠 24
     4.3 C電子零組件廠（開關零件） 31
     4.4 D電子零組件廠（端子台） 36
     4.5 跨個案分析 42
     第五章 結論與建議 49
     5.1 研究發現 49
     5.2 管理意涵 52
     5.3 研究貢獻 53
     5.4 研究限制與未來建議 53
     參考文獻 54		zh_TW
dc.source.uri (資料來源) http://thesis.lib.nccu.edu.tw/record/#G0105363112en_US
dc.subject (關鍵詞) 工業4.0zh_TW
dc.subject (關鍵詞) TOE架構zh_TW
dc.subject (關鍵詞) 新科技採行zh_TW
dc.subject (關鍵詞) 意圖zh_TW
dc.subject (關鍵詞) Industry 4.0en_US
dc.subject (關鍵詞) TOE frameworken_US
dc.subject (關鍵詞) New technology adoptingen_US
dc.subject (關鍵詞) Intentionen_US
dc.title (題名) 以TOE架構探討影響企業採行工業4.0意圖之因素zh_TW
dc.title (題名) Factors influencing the intention of industry 4.0 adoption: A TOE framework perspectiveen_US
dc.type (資料類型) thesisen_US
dc.relation.reference (參考文獻) 英文部分
     1. Aboelmaged, M. G. (2014). Predicting e-readiness at firm-level: An analysis of technological, organizational and environmental (TOE) effects on e-maintenance readiness in manufacturing firms. International Journal of Information Management, 34(5), 639-651.
     2. Dilberoglu, U. M., Gharehpapagh, B., Yaman, U., & Dolen, M. (2017). The role of additive manufacturing in the era of industry 4.0. Procedia Manufacturing, 11, 545-554.
     3. Gartner (2016). Gartner’s Top 10 Strategic Technology Trends for 2017. https://www.gartner.com/smarterwithgartner/gartners-top-10-technology-trends-2017/
     4. Ghobakhloo, M., Arias-Aranda, D., & Benitez-Amado, J. (2011). Adoption of e-commerce applications in SMEs. Industrial Management & Data Systems, 111(8), 1238-1269.
     5. Giusto, D., Iera, A., Morabito, G., & Atzori, L. (Eds.). (2010). The internet of things: 20th Tyrrhenian workshop on digital communications. Springer Science & Business Media.
     6. Gutierrez, A., Boukrami, E., & Lumsden, R. (2015). Technological, organisational and environmental factors influencing managers’ decision to adopt cloud computing in the UK. Journal of Enterprise Information Management, 28(6), 788-807.
     7. Hermann, M., Pentek, T., & Otto, B. (2016, January). Design principles for industrie 4.0 scenarios. In System Sciences (HICSS), 2016 49th Hawaii International Conference on (pp. 3928-3937). IEEE.
     8. Kagermann, H., Helbig, J., Hellinger, A., & Wahlster, W. (2013). Recommendations for implementing the strategic initiative INDUSTRIE 4.0: Securing the future of German manufacturing industry; final report of the Industrie 4.0 Working Group. Forschungsunion.
     9. Kuan, K. K., & Chau, P. Y. (2001). A perception-based model for EDI adoption in small businesses using a technology–organization–environment framework. Information & management, 38(8), 507-521.
     10. Kumar, K. N., Chandra, S., Bharati, S., & Manava, S. (2016, June). Factors Influencing Adoption of Augmented Reality Technology for E-Commerce. In PACIS (p. 342).
     11. Lasi, H., Fettke, P., Kemper, H. G., Feld, T., & Hoffmann, M. (2014). Industry 4.0. Business & Information Systems Engineering, 6(4), 239-242.
     12. Lee, E. A. (2008, May). Cyber physical systems: Design challenges. In 11th IEEE Symposium on Object Oriented Real-Time Distributed Computing (ISORC) (pp. 363-369). IEEE.
     13. Nunes, M. L., Pereira, A. C., & Alves, A. C. (2017). Smart products development approaches for Industry 4.0. Procedia Manufacturing, 13, 1215-1222.
     14. Lu, Y. (2017). Industry 4.0: A survey on technologies, applications and open research issues. Journal of Industrial Information Integration, 6, 1-10.
     15. Lucke, D., Constantinescu, C., & Westkämper, E. (2008). Smart factory-a step towards the next generation of manufacturing. In Manufacturing systems and technologies for the new frontier (pp. 115-118). Springer, London.
     16. McKinsey. (2016). Industry 4.0 after the initial hype- Where manufacturers are finding value and how they can best capture it. McKinsey Digital 2016. https://www.mckinsey.com/business-functions/operations/our-insights/industry-40-looking-beyond-the-initial-hype
     17. 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.
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dc.identifier.doi (DOI) 10.6814/THE.NCCU.MBA.055.2018.F08-