應用文字探勘與科技機會分析探索物聯網物流服務

Abstract

近二十年來，隨著科技技術的快速進步，“物聯網”（Internet of Things - IoT）的概念除了在學術上的探討外，亦開始出現在人們生活應用上。例如：智慧家庭、智慧建築、智慧零售……等。人們對於物聯網相關的技術和服務越來越為熟悉，有鑒於此，物聯網的分析和未來預測對於學術研究人員和從業者有著至關重要的影響。近年來，許多物聯網的技術應用在物流產業中，其中對於航運，空運，倉儲，庫存等產業的影響也舉足輕重。 對於探索物聯網技術的機會以及針對物聯網技術進行預測對於物聯網的整體發展至關重要，並且目前已有相當多種技術或方法可以針對物聯網技術進行深入研究。本研究中的數據分析和文字探勘技術，針對探索物聯網技術的機會和技術服務演進分析已被應用於分析和觀察物聯網技術和服務演進。同時，學術期刊、市場報告和專利已針對物流領域中的物聯網技術有深入研究及審查；而過往收集的物聯網學術研究和市場報告將是本研究的核心。此外，分析物聯網的技術機會，以探索基於物聯網的物流服務，例如：利用雲技術開發智能物流服務、利用RFID技術開發信息物流服務。最後，通過將初始結構化數據以及其他所有文檔的非結構化和半結構化數據相結合，進一步可以觀察到物聯網技術和服務演進。總體而言，本研究的結果將提供有關物聯網在物流服務上的方法指導，以便全面了解相關發展及未來方向；並希望能提高整體效益，可提出標準化的商業模式給予實務業界做為參考與指引。

As technological advancements surge in recent years, the concept of Internet of Things has emerged in the society in the past decade. Internet of Things’ (IoT) related technologies and services have become more familiar to people, thus analysis and future forecasting on IoT is vital and beneficial to guide both scholars and practitioners. Many IoT technologies have been applied in the logistics industry in recent years and they performed substantial impact in many sectors such as shipping, air freight, warehousing and inventory etc. Exploring technology opportunities and carrying out technological forecasting is essential for IoT‘s rapid changes and there are manifold of techniques or methods to do so. Herein, data and text mining techniques, technology opportunity analysis and technology-service evolution analysis have been applied for analysis and observing IoT technologies and services evolutions. Academic journals, market reports and patents have been reviewed on the topic of IoT in logistics field; collecting academic-based and market-based documents supports the provision of a comprehensive overview of this study. Moreover, technology opportunities have been analyzed to explore IoT-based logistics services, for example with the use of cloud technology to develop smart logistics services, or with the RFID technology to develop information logistics services. Lastly, it enables the observation of IoT technology and service evolutions by combining initial structured data with unstructured and semi-structured data from all documents. In summary, results of this study will provide methodological guidelines on this topic for a comprehensive understanding; aiming to increase productivity as a whole and coming up with a standardized business model for timely use.