本課程旨在帶領學員回歸「服務科學的本質」，探討在數位轉型與 AI 浪潮下，服務系統如何透過「價值共創」機制，重新定義企業與消費者的關係。我們將超越技術崇拜，從跨領域視角解析服務主導邏輯（Service-Dominant Logic），建立紮實的理論框架。
課程核心上半部旨在運用服務科學（Service Science）的理論透鏡，解構五家不同領域的全球服務業巨頭如何建構其競爭優勢。研究發現，無論是金融資本的配置（Berkshire）、醫療生態的整合（UnitedHealth）、娛樂體驗的串流化（Netflix）、財富傳承的信任管理（UBS），抑或是旅遊平台的連結策略（Booking），其成功的核心皆在於從「交易」轉向「關係」，從「產品交付」轉向「價值共創」，並展現出卓越的「動態能力」以適應數位經濟的演化。
學期下半部採用高強度的美國科技(服務)公司個案研討（Case Discussion）。我們將深入剖析矽谷頂尖企業的 AI 創新路徑，包括：Palantir 如何將數據轉化為決策服務、Alphabet 以Gemini為核心的雲端生態系整合、提供算力基礎設施的 Nvidia、Upstart 的 AI 金融信貸評估、CrowdStrike 的主動式資安防禦，以及 SoundHound AI 的自然語言即時轉譯。
不同於傳統的技術分析，本課程將嚴謹地站在「消費者立場」進行批判性辯證。我們將挑戰學員思考：這些所謂的創新，究竟解決了哪些務實需求（Pain Points）？例如，Upstart 的演算法是否真能比傳統信評更普惠且準確？SoundHound 的語音互動是提升了效率，還是增加了認知負荷？同時，我們也將檢視哪些高昂的 AI 投資僅是技術堆疊，最終可能因缺乏商業落地場景而淪為泡沫與浪費。
透過本課程，學員將獲得穿透技術迷霧的洞察力，學會區辨「炒作」與「實質創新」，並能將這些國際標竿的成敗經驗，轉化為自身企業服務轉型的戰略智慧。
《 課程簡介 -- English 》
This course aims to guide students back to the essence of Service Science, exploring how service systems redefine the relationship between enterprises and consumers through "value co-creation" mechanisms amidst the wave of digital transformation and AI. Moving beyond mere technological worship, we will analyze Service-Dominant Logic from an interdisciplinary perspective to build a robust theoretical framework.
At its core, the course features intensive case discussions focused on leading U.S. technology and service companies. We will dissect the AI innovation trajectories of top Silicon Valley firms, including: Palantir’s transformation of data into decision-making services; Alphabet’s cloud ecosystem integration centered on Gemini; Nvidia’s provision of computing infrastructure; Upstart’s AI-driven financial credit assessment; CrowdStrike’s proactive cybersecurity defense; and SoundHound AI’s real-time natural language translation.
Distinguishing itself from traditional technical analysis, this course adopts a rigorous "consumer-centric" perspective to foster critical examination. We will challenge students to reflect on the following: Which practical needs (pain points) do these so-called innovations actually address? For instance, are Upstart’s algorithms truly more inclusive and accurate than traditional credit ratings? Does SoundHound’s voice interaction enhance efficiency or merely increase cognitive load? Simultaneously, we will scrutinize which costly AI investments are merely "tech stacks" that risk becoming bubbles and waste due to a lack of viable commercial application scenarios.
Through this course, students will gain the insight needed to pierce through the technological fog, learning to distinguish between "market hype" and "substantive innovation." Ultimately, they will be able to translate the experiences—both successes and failures—of these international benchmarks into strategic wisdom for their own enterprise's service transformation.
|