新的產業趨勢造成經濟版圖的變化，近幾年AIoT（Artificial Intelligence of Things，智聯網）的議題迅速展開數位轉型與價值創新，重要性讓各國政府制定國家策略倡議其影響層級，興起的動能帶給臺灣擅於設計與製造的資通訊業產生龐大挑戰及契機，面對這波長期趨勢改變，大型企業必須進行優化數位能力來因應。

新數位科技物聯網結合人工智慧，兩種技術宛如神經元與大腦相輔而成，物聯感測及行動裝置提供可用地巨量資料，藉由不同網路拓樸將資料數據傳送到平台層伺服器群集，提供給AI進行學習、演算法分析與判斷、以及產生精準預測模擬，衍生的服務應用涵蓋各行業領域，像是：智慧工廠、智慧城市、智慧家庭、智慧醫療等，大型企業商業策略必須根據產業變動而改變，採擷新興數位資訊科技來適應。

本研究旨在探討目前AIoT數位科技對大型企業之影響及實行現況，透過學者文獻與AIoT演化歷程以TOE理論框架建構問卷量表題項，有效回收的專家問卷經因素分析得到三個高解釋量的共同因子，再運用區別分析法檢測兩分群，得到領先組企業與一般組企業的標準化區別函數，研究結果歸納出實施AIoT關鍵成功要素，提供企業實務上調整商業策略參考。

A novel industrial trend has ushered in dramatic changes to the global economic landscape. In recent years, AIoT (Artificial Intelligence of Things) related topics have rapidly triggered the megatrends of digital transformation and value innovation. Thus, it is indispensable for global governments to develop national strategies and advocate the significant influence. The emerging momentum would bring business opportunities as well as challenges for Taiwan ITC industry that is good at designing and manufacturing. To address the long-term and drastic global changes, enterprises must optimize their digital capabilities to tackle the impending transformation.

New digital technology of IoT leveraged with AI can be likened to be the biological synergy created by neurons and brains. IoT sensors work in tandem with mobile devices to provide tremendous amount of raw data transmitted through individual network topology to the server clusters over the platform layer, where AI programs undertake tasks of learning, algorithm analysis and decision making, allowing to develop a model of simulation with diverse services & applications across multiple industries such as smart manufacturing, smart cities, smart homes, smart healthcare etc... Large enterprises need to step up meaningful innovative digital strategies to usher in the new industrial era.

The purpose of this study is to delve into the current impact of AIoT digital technologies on large enterprises and the status of its implementation. The questionnaires were based on the framework of TOE theory and developed through scholars’literature alongside with the evolution of AIoT. Three highly-explainable common factors found through the Factor Analysis from the collected valid data of expert questionnaires. The Discriminant Analysis was adopted to come up with the Standardized Discriminant Function Coefficients of two categories：significantly ahead and on par. Eventually, this research investigation has illustrated the key factors to the implementation of AIoT technologies, providing a meaningful reference for enterprises to adapt their business strategies.

1.中文文獻
人工知能技術戰略. (2017). (日本人工智能技術戰略委員會).
吳明隆. (2010). 論文寫作與量化研究. 150-155.
新一代人工智能發展規畫. (2017). (中國國務院).
鄭宇庭, 李政豫, & 余清祥. (2014). 量化專家意見與人口推估. 人口學刊(49), 41-68.

2.英文文獻
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.
Adebayo, A. O., Chaubey, M. S., & Numbu, L. P. (2019). Industry 4.0： The Fourth Industrial Revolution And How It Relates To The Application Of Internet Of Things (IoT). Journal of Multidisciplinary Engineering Science Studies, 5, 2477-2478.
Agarwal, N., & Brem, A. (2015). Strategic business transformation through technology convergence: implications from General Electric's industrial internet initiative. International Journal of Technology Management, 67(2-4), 196-214.
Albukhitan, S. (2020). Developing Digital Transformation Strategy for Manufacturing. Procedia Computer Science, 170, 664-671.
Altmaier, P. (2019). National Industrial Strategy 2030: Strategic Guidelines for a German and European Industrial Policy. In: Berlin: Federal Ministry for Economic Affairs and Energy.
Announcing AWS Inferentia: Machine Learning Inference Chip. (2018). (AMAZON).
Artificial Intelligence Strategy. (2018). (The Federal Government).
Ashton, K. (2009). That ‘Internet of Things’ Thing. RFID journal, 22(7), 97-114.
Banerjee, D. (2018). A microarchitectural study on apple’s a11 bionic processor. Arkansas State University: Jonesboro, AR, USA.
Björkdahl, J. (2020). Strategies for digitalization in manufacturing firms. California management review, 62(4), 17-36.
Bonomi, F. (2011). Cloud and Fog Computing: Trade-Offs and Applications. (EON-2011 Workshop, International Symposium on Computer Architecture (ISCA 2011)).
Bonomi, F., Milito, R., Zhu, J., & Addepalli, S. (2012). Fog computing and its role in the internet of things. Paper presented at the Proceedings of the first edition of the MCC workshop on Mobile cloud computing.
Boyes, H., Hallaq, B., Cunningham, J., & Watson, T. (2018). The industrial internet of things (IIoT): An analysis framework. Computers in Industry, 101, 1-12.
Brock, J. K.-U., & Von Wangenheim, F. (2019). Demystifying AI: What digital transformation leaders can teach you about realistic artificial intelligence. California management review, 61(4), 110-134.
Chettri, L., & Bera, R. (2020). A Comprehensive Survey on Internet of Things (IoT) Toward 5G Wireless Systems. IEEE Internet of Things Journal, 7(1), 16-32. doi:10.1109/JIOT.2019.2948888
Chiang, M., & Zhang, T. (2016). Fog and IoT: An overview of research opportunities. IEEE Internet of Things Journal, 3(6), 854-864.
Chiu, C.-Y., Chen, S., & Chen, C.-L. (2017). An integrated perspective of TOE framework and innovation diffusion in broadband mobile applications adoption by enterprises. International Journal of Management, Economics and Social Sciences (IJMESS), 6(1), 14-39.
Christensen, C. M. (1992a). Exploring the limits of the technology S‐curve. Part I: component technologies. Production and operations management, 1(4), 334-357.
Christensen, C. M. (1992b). Exploring the limits of the technology S‐curve. Part II: Architectural technologies. Production and operations management, 1(4), 358-366.
Cisco Annual Internet Report 2018-2023. (2020). (Cisco public).
Classic Paper Award Recipient：John McDermott. (1999). (Association for the Advancement of Artificial Intelligence).
Dahlqvist, F., Patel, M., Rajko, A., & Shulman, J. (2019). Growing opportunities in the Internet of Things. McKinsey, July.
De Donno, M., Tange, K., & Dragoni, N. (2019). Foundations And Evolution Of Modern Computing Paradigms: Cloud, IoT, Edge, and Fog. IEEE access, 7, 150936-150948.
Deng, J., Dong, W., Socher, R., Li, L.-J., Li, K., & Fei-Fei, L. (2009). Imagenet: A large-scale hierarchical image database. Paper presented at the 2009 IEEE conference on computer vision and pattern recognition.
Denzin, N. K. (1970). The Research Act: A Theoretical Introduction to Sociological Methods: Aldine Publishing Company.
Dustdar, S., Avasalcai, C., & Murturi, I. (2019, 4-9 April 2019). Invited Paper: Edge and Fog Computing: Vision and Research Challenges. Paper presented at the 2019 IEEE International Conference on Service-Oriented System Engineering (SOSE).
Elazhary, H. (2019). Internet of Things (IoT), mobile cloud, cloudlet, mobile IoT, IoT cloud, fog, mobile edge, and edge emerging computing paradigms: Disambiguation and research directions. Journal of Network and Computer Applications, 128, 105-140.
Etzion, O. (2015). When artificial intelligence meets the internet of things. Paper presented at the Proceedings of the 9th ACM International Conference on Distributed Event-Based Systems.
Facebook says its new Instagram-trained A.I. represents a big leap forward for computer vision. (2021).
Fathers of the Deep Learning Revolution Receive ACM A. M. Turing Award. (2019). In: ACM New York, NY, USA.
Felipe, C. M., Roldán, J. L., & Leal-Rodríguez, A. L. (2016). An explanatory and predictive model for organizational agility. Journal of Business Research, 69(10), 4624-4631.
Foster, R. N. (1982a). Effective R&D Operations in the'80s: Boosting The Payoff From R&D. Research management, 25(1), 22-27.
Foster, R. N. (1986). Innovation: the Attacker’s Advantage. In: EQUIPMENT/METHODS INNOVATION.
Hair, J. F., Sarstedt, M., Ringle, C. M., & Mena, J. A. (2012). An assessment of the use of partial least squares structural equation modeling in marketing research. Journal of the academy of marketing science, 40(3), 414-433.
Han, D., Wu, S., Hu, Z., Gao, H., Liu, E., & Lu, Y. (2021). A Novel Classified Ledger Framework for Data Flow Protection in AIoT Networks. Security and Communication Networks, 2021. doi:10.1155/2021/6671132
Hopfield, J. J. (1982). Neural networks and physical systems with emergent collective computational abilities. Proceedings of the national academy of sciences, 79(8), 2554-2558.
Hopfield, J. J. (1984). Neurons with graded response have collective computational properties like those of two-state neurons. Proceedings of the national academy of sciences, 81(10), 3088-3092.
IEEE Standard for Adoption of OpenFog Reference Architecture for Fog Computing. (2018). (IEEE Std 1934™-2018 ).
IEEE Standard for Broadband over Power Line Networks: Medium Access Control and Physical Layer Specifications. (2010). IEEE Std 1901-2010, 1-1586. doi:10.1109/IEEESTD.2010.5678772
ImageNet Large Scale Visual Recognition Challenge (ILSVRC). (2020). ( Stanford Vision Lab, Stanford University, Princeton University).
The Internet of Things: Executive Summary. (2005). (The International Telecommunication Union, ITU).
The Internet Of Things：a movement ,not a market. (2017). (IHS Markit ).
Iorga, M., Feldman, L., Barton, R., Martin, M. J., Goren, N. S., & Mahmoudi, C. (2018). Fog computing conceptual model.
IoT Growth Demands Rethink of Long-Term Storage Strategies, says IDC. (2020). (International Data Corporation,IDC).
ITU. (2012). Overview of the Internet of things (The International Telecommunication Union, ITU), 1-3.
ITU. (2021). Framework for Internet of things ecosystem master plan. (The International Telecommunication Union, ITU), 6-7.
Jamali, M. A. J., Bahrami, B., Heidari, A., Allahverdizadeh, P., & Norouzi, F. (2020). IoT architecture. Towards the Internet of Things, 9-31.
James, L. (1973). Artificial Intelligence: A general survey. Science Research Council.
Jetson TX2 Module.
Jones, O., & Gatrell, C. (2014). The future of writing and reviewing for IJMR. In: Wiley Online Library.
Jouppi, N. (2016). Google supercharges machine learning tasks with TPU custom chip.
Kaplan, A., & Haenlein, M. (2019). Siri, Siri, in my hand: Who’s the fairest in the land? On the interpretations, illustrations, and implications of artificial intelligence. Business Horizons, 62(1), 15-25.
Karner, M., Hillebrand, J., Klocker, M., & Sámano-Robles, R. (2021, 1-3 Sept. 2021). Going to the Edge - Bringing Internet of Things and Artificial Intelligence Together. Paper presented at the 2021 24th Euromicro Conference on Digital System Design (DSD).
Kato, I. (1973). Humanoid History -WABOT. (Waseda University).
Keivani, A., Ghayoor, F., & Tapamo, J.-R. (2021). Collaborative Mobile Edge Computing in eV2X: A Solution for Low-Cost Driver Assistance Systems. Wireless Personal Communications, 118(3), 1869-1882. doi:10.1007/s11277-019-06401-2
Krizhevsky, A., Sutskever, I., & Hinton, G. E. (2012). Imagenet classification with deep convolutional neural networks. Advances in neural information processing systems, 25, 1097-1105.
Kuguoglu, B. K., van der Voort, H., & Janssen, M. (2021). The Giant Leap for Smart Cities: Scaling Up Smart City Artificial Intelligence of Things (AIoT) Initiatives. Sustainability, 13(21), 12295.
Lichtenthaler, U. (2018). Beyond artificial intelligence: Why companies need to go the extra step. Journal of Business Strategy.
Matter is the foundation for connected things. (2021). (Connectivity Standards Alliance (CSA)).
McCarthy, J., Minsky, M. L., Rochester, N., & Shannon, C. E. (1955). A Proposal For The Dartmouth Summer Research Project On Artificial Intelligence, August 31, 1955. AI magazine, 27(4), 12-12.
McDermott, J. P. (1980). RI: an Expert in the Computer Systems Domain. Paper presented at the AAAI.
Mell, P., & Grance, T. (2011). The NIST Definition Of Cloud Computing. (National Institute of Standards and Technology,NIST).
Miller, G. A. (1995). WordNet: a lexical database for English. Commun. ACM, 38(11), 39–41. doi:10.1145/219717.219748
Minsky, M., & Papert, S. A. (1969). Perceptrons: An introduction to computational geometry: MIT press.
National AI Strategy. (2021).
The National Artificial Intelligence Initiative (NAII). (2020). (National AI Initiative).
The National Artificial Intelligence Research And Development Strategic Plan. (2019). (National Science & Technology Council).
Orsini, J.-F. (1986). Artificial intelligence: A way through the strategic planning crisis? Long Range Planning, 19(4), 71-77.
Panduman, Y. Y. F., Sukaridhoto, S., & Tjahjono, A. (2019). A Survey of IoT Platform Comparison for Building Cyber-Physical System Architecture. Paper presented at the 2019 International Seminar on Research of Information Technology and Intelligent Systems (ISRITI).
Park, H., Kim, H., Joo, H., & Song, J. (2016). Recent advancements in the Internet-of-Things related standards: A oneM2M perspective. ICT Express, 2(3), 126-129.
Pfeffer, J., & Sutton, R. I. (2006). Profiting From Evidence‐based Management. Strategy & Leadership.
Raff, S., Wentzel, D., & Obwegeser, N. (2020). Smart products: conceptual review, synthesis, and research directions. Journal of Product Innovation Management, 37(5), 379-404.
Rahmani, A. M., Gia, T. N., Negash, B., Anzanpour, A., Azimi, I., Jiang, M., & Liljeberg, P. (2018). Exploiting smart e-Health gateways at the edge of healthcare Internet-of-Things: A fog computing approach. Future Generation Computer Systems, 78, 641-658.
Recommendations for implementing the strategic initiative INDUSTRIE 4.0. (2013). (Forschungsunion, acatech).
Rosenblatt, F. (1961). Principles of Neurodynamics. perceptrons and the theory of brain mechanisms. Retrieved from
Rumelhart, D. E., Hinton, G. E., & Williams, R. J. (1986). Learning representations by back-propagating errors. nature, 323(6088), 533-536.
Sabry, S. S., Qarabash, N. A., & Obaid, H. S. (2019, 13-15 March 2019). The Road to the Internet of Things: a Survey. Paper presented at the 2019 9th Annual Information Technology, Electromechanical Engineering and Microelectronics Conference (IEMECON).
Sayginer, C., & Ercan, T. (2020). Understanding determinants of cloud computing adoption using an integrated diffusion of innovation (Doi)-technological, organizational and environmental (TOE) model. Humanities & Social Sciences Reviews, 8(1), 91-102.
Searle, J. R. (1980). Minds, brains, and programs. Behavioral and brain sciences, 3(3), 417-424.
Shefer, D., & Frenkel, A. (2005). R&D, Firm Size And Innovation: An Empirical Analysis. Technovation, 25(1), 25-32.
Shi, W., Cao, J., Zhang, Q., Li, Y., & Xu, L. (2016). Edge computing: Vision and challenges. IEEE Internet of Things Journal, 3(5), 637-646.
Shrouf, F., Ordieres, J., & Miragliotta, G. (2014, 9-12 Dec. 2014). Smart factories in Industry 4.0: A review of the concept and of energy management approached in production based on the Internet of Things paradigm. Paper presented at the 2014 IEEE International Conference on Industrial Engineering and Engineering Management.
Silver, D., Huang, A., Maddison, C. J., Guez, A., Sifre, L., Van Den Driessche, G., . . . Lanctot, M. (2016). Mastering the game of Go with deep neural networks and tree search. nature, 529(7587), 484-489.
Siriwardhana, Y., Gür, G., Ylianttila, M., & Liyanage, M. (2021). The role of 5G for digital healthcare against COVID-19 pandemic: Opportunities and challenges. ICT Express, 7(2), 244-252.
Sjödin, D., Parida, V., Palmié, M., & Wincent, J. (2021). How AI capabilities enable business model innovation: Scaling AI through co-evolutionary processes and feedback loops. Journal of Business Research, 134, 574-587. doi:10.1016/j.jbusres.2021.05.009
Song, H., Bai, J., Yi, Y., Wu, J., & Liu, L. (2020). Artificial Intelligence Enabled Internet of Things: Network Architecture and Spectrum Access. IEEE Computational Intelligence Magazine, 15(1), 44-51. doi:10.1109/MCI.2019.2954643
Stewart, J. C., Davis, G. A., & Igoche, D. A. (2020). AI, IoT, AND AIoT: DEFINITIONS AND IMPACTS ON THE ARTIFICIAL INTELLIGENCE CURRICULUM. Issues in Information Systems, 21(4).
Tappert, C. C. (2019, 5-7 Dec. 2019). Who Is the Father of Deep Learning? Paper presented at the 2019 International Conference on Computational Science and Computational Intelligence (CSCI).
Tornatzky, L. G., Fleischer, M., & Chakrabarti, A. K. (1990). Processes of Technological Innovation: Lexington books.
Turing, A. M. (1950). Computing Machinery and Intelligence. Mind, 59(236), 433-460.
Ven, K., & Verelst, J. (2011). An empirical investigation into the assimilation of open source server software. Communications of the association for information systems, 28(1), 9.
Von Der Gracht, H., Huber-Straßer, A., Schüller, M., Müller, N., Lichtenau, P., & Zühlke, H. (2018). Rethinking The Value Chain. A study on AI, Humanoids And Robots - Artificial Intelligence: Possible Business Application And Development Scenarios To 2040: KPMG.
Wang, D., Chen, D., Song, B., Guizani, N., Yu, X., & Du, X. (2018). From IoT to 5G I-IoT: The Next Generation IoT-Based Intelligent Algorithms and 5G Technologies. IEEE Communications Magazine, 56(10), 114-120. doi:10.1109/MCOM.2018.1701310
Wazid, M., Das, A. K., & Park, Y. (2021). Blockchain-Envisioned Secure Authentication Approach in AIoT: Applications, Challenges, and Future Research. Wireless Communications and Mobile Computing, 2021.
Weiser, M. (1991). The Computer for the 21 st Century. Scientific american, 265(3), 94-105.
Weizenbaum, J. (1966). ELIZA—a computer program for the study of natural language communication between man and machine. Communications of the ACM, 9(1), 36-45.
Werbos, P. (1974). Beyond Regression: New Tools for Prediction and Analysis in the Behavioral Science. Ph. D. dissertation, Harvard University.
Wu, Y. C., Wu, Y. J., & Wu, S. M. (2019). An outlook of a future smart city in Taiwan from post–internet of things to artificial intelligence internet of things. In Smart Cities: Issues and Challenges (pp. 263-282): Elsevier.
Yin, J., Wei, S., Chen, X., & Wei, J. (2020). Does it pay to align a firm’s competitive strategy with its industry IT strategic role? Information & Management, 57(8), 103391.
Yu, W., Liang, F., He, X., Hatcher, W. G., Lu, C., Lin, J., & Yang, X. (2017). A Survey On The Edge Computing For The Internet of Things. IEEE access, 6, 6900-6919.
Zheng, H., Lin, F., Feng, X., & Chen, Y. (2021). A Hybrid Deep Learning Model With Attention-Based Conv-LSTM Networks for Short-Term Traffic Flow Prediction. IEEE Transactions on Intelligent Transportation Systems, 22(11), 6910-6920. doi:10.1109/TITS.2020.2997352
Zhu, K., Dong, S., Xu, S. X., & Kraemer, K. L. (2006). Innovation diffusion in global contexts: determinants of post-adoption digital transformation of European companies. European journal of information systems, 15(6), 601-616.