近年來，一般低售價產品已不是消費者決定購買產品的主要決策考量，相反的，顧客體驗、高附加價值服務以及具永續性之產品更具有競爭力，而這些也正是產品服務系統(PSS)具備之特性。隨著智能和互聯產品的快速發展，它使產品服務提供商能夠以更靈活、更精確和個性化的方式提供價值，而智能產品服務系統（Smart PSS）結合了有形產品，無形服務和網路等後端支持系統以提高實用性並滿足不同客戶需求，被視為新的解決方案。在過去幾年中，雖已有關於如何設計與應用智能產品服務系統的研究，但因其設計會因為產業、產品型式、營運模式等多方因素而產生不同的結果，其變動性也使得沒有一套方法能套用至每個案例，因此仍有機會改進設計方法，以便為不斷變化的環境提供不同的洞察力。
有鑑於大數據時代，本文提出了一個以數據為驅動之智能產品服務系統設計框架：1.利用文字分析技術捕獲產品服務系統改進機會 、 2.根據產品服務系統設計流程以服務藍圖呈現和數據驅動技術提出改進計劃、 3.通過即時顧客參與資訊以提供智能服務。本研究的主要目的是希望能為服務提供商提供改進服務設計流程的見解。研究的貢獻包括數據驅動改進項目的逐步演示、機器學習技術的導入以及結合多種資料分析手法之詳細案例分析，此外，過往研究大多著重在討論科技技術的發展如何影響智能產品服務系統之設計，本研究更將探討顧客的參與以及產品產生之資料如何能與構建智能產品服務系統產生正面影響。

Over the years, simply low-cost products are no longer be the main attraction to customers. Instead, high value-added products draw new attention. With the rapid advance of smart and connected product, it enables service provider to deliver services in a more flexible, precise and personalized way. Considered as a solution to the strategy, the Smart Product Service System (Smart PSS) integrates tangible products, intangible services, and IoT based back-end support systems to improve the versatility and meet diverse customer needs. Although many studies have addressed on traditional PSS design, how to coordinate new technologies to achieve Smart PSS that can response to changing environment remains absent. Additionally, the variability of smart PSSs also makes impossible to apply to every case, no matter how complicated the design method is. Therefore, the aim of this study is to provide insights for service providers on improving the service design process in this data-intensive era.
We proposed a systematic framework by 1) Utilizing text analytic technique to capture PSS via service blueprint to capture improvement opportunities. 2) Proposing an improvement plan under PSS design process and data-driven techniques. And 3) offering smart services by cooperating with customers’ real time data. The contribution of the study included a step-by-step demonstration of data-driven improvement project based on machine learning technique, with a detailed case study combining multiple data analysis techniques. Further, this study will also explore how customer engagement and product-generated information can have a positive impact on building smart product service systems.

Abstract II
Table of Contents IV
List of Figures V
List of Tables V
1 Introduction 6
2 Literature Review 8
2.1 Design of Product Service System 8
2.2 Design of Smart Product Service System 11
2.3 Value Co-creation and Co-production 15
3 Methodology 18
3.1 Identify Customers’ Requirement 19
3.2 Analyze Improvement Opportunities 21
3.3 Develop Solutions 23
4 Case Study 26
4.1 Identify Customers’ Requirement on Ubike© 26
4.2 Analyze Improvement Opportunities 28
4.3 Develop Solutions 32
4.5 Discussion 45
5 Conclusion 49
6 References 52
7 APPENDIX 57

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