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Title: | 我國金融科技發展預測:以QR Code支付應用為例 Technological Forecasting for the Development of QR Code Applications in Taiwan’s FinTech Field |
Authors: | 劉邦宇 Liu, Bang-Yu |
Contributors: | 吳豐祥 Wu, Feng-Shang 劉邦宇 Liu, Bang-Yu |
Keywords: | QR Code支付 技術預測 成長曲線法 技術生命週期 專利分析 QR code-based payment Technology forecasting Growth curve approach Technology lifecycle Patent data analysis |
Date: | 2025 |
Issue Date: | 2025-07-01 14:33:02 (UTC+8) |
Abstract: | 本研究旨在探討我國金融科技領域中QR Code支付應用技術之發展趨勢,並透過專利資料進行技術預測,以提供金融機構與政策制定者未來發展之策略參考。研究問題包括探討本技術適合之技術預測模型、判斷本技術現所屬的生命週期階段,並分析產業上技術應用布局之情形。
在研究方法上,本研究蒐集並篩選QR Code支付應用技術的相關專利,並藉由技術生命週期理論,以Logistic模型與Gompertz模型進行成長曲線的趨勢預測分析。模型適配性與預測能力的評估標準則透過R²與MAPE兩項統計指標進行分析與比較。
本研究所得到的主要發現,包括: 一、QR Code支付應用技術預測模型的建構上,Gompertz model展現出比Logistic model更高的適配程度及更佳的預測能力。 二、QR Code支付應用技術專利發展高度依賴外部環境,初期受政策推動而快速成長,後期的成長則因疫情與資源轉移而趨緩。 三、以專利資料觀之,現階段QR Code支付技術的應用領域以銀行經營上的轉帳、繳費/繳稅、提款等業務為主。 四、QR Code支付應用技術的專利申請人以銀行業者為主。 五、在各類專利的比重上,不同於我國整體以發明專利為主,在QR Code支付應用技術的專利申請上是以新型專利為主。
參考上述的研究發現,本研究建議業者未來可以考量更積極地投入資源於購物及乘車等貼近日常生活的應用場景,並透過跨界合作、技術授權與專利布局策略來強化市場競爭力。此外,本研究也建議政府提供更靈活的政策支持與激勵措施,促進業界對於創新技術的研發投入,以避免QR Code支付技術過早進入衰退期,確保技術的持續創新與產業的永續發展。
本研究主要學術上的貢獻,包括: 一、透過分析確認了Gompertz model與Logistic model的比較優勢,研究結果彌補了過往文獻有關預測模型選擇無定論的缺口。 二、從技術預測的觀點來探討QR Code支付應用技術的發展,研究結果彌補了過往該領域文獻較偏向於政策、應用與推廣策略等面向的研究缺口。 This thesis aims to investigate the development trends of QR Code payment application technologies within Taiwan's financial technology sector and employs patent data to perform technological forecasting. The findings aim to provide strategic references for financial institutions and policy-makers. The research questions include identifying suitable technological forecasting models for QR Code payment technology, determining its current lifecycle stage, and analyzing the industry's technological application landscape.
In terms of methodology, this thesis collects and screens patents related to QR Code payment applications and employs technological lifecycle theory, utilizing Logistic and Gompertz models for growth curve forecasting analysis. Model suitability and predictive performance are evaluated and compared using statistical indicators R² and MAPE.
The main findings of this thesis are: 1.The Gompertz model demonstrates a higher degree of fit and better predictive capability compared to the Logistic model in constructing forecasting models for QR Code payment application technologies. 2.The patent development of QR Code payment technology is highly dependent on the external environment. Initially, rapid growth was driven by policy support, whereas later growth slowed due to the pandemic and resource reallocation. 3.Currently, the predominant application domains of QR Code payment technology patents involve banking operations, such as fund transfers, bill/tax payments, and cash withdrawals. 4.Banks represent the primary group of patent applicants for QR Code payment application technologies. 5.Unlike the broader Taiwanese patent landscape dominated by invention patents, QR Code payment application technology patents predominantly consist of utility model patents.
Based on these findings, this thesis suggests that firms should actively invest resources in applications closely related to daily life, such as shopping and transportation, and enhance market competitiveness through cross-industry collaboration, technology licensing, and strategic patent portfolios. Additionally, the government is recommended to provide flexible policy support and incentives to stimulate innovation and prevent the premature decline of QR Code payment technologies, thereby ensuring sustained technological innovation and industry sustainability.
The key academic contributions of this thesis include: 1.Confirming the comparative advantages of the Gompertz and Logistic models, addressing gaps in existing literature regarding inconclusive model selection. 2.Exploring the development of QR Code payment application technologies from a technological forecasting perspective, thus addressing literature gaps primarily focused on policy, application, and promotion strategies in this field. |
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Description: | 碩士 國立政治大學 科技管理與智慧財產研究所 112364218 |
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