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標題: | AI圖像辨識在美髮沙龍產業應用之商業模式與創新 Business Model and Innovation of AI Image Recognition in the Hair Salon Industry |
作者: | 陳俊偉 Chun-Wei Chen |
指導教授: | 魏志平 Chih-Ping Wei |
關鍵字: | 美髮沙龍,頭皮養護,AI圖像辨識,人工智慧,商業模式,數據競爭力,頭皮檢測系統, Hair Salon,Scalp Care,AI Image Recognition,Artificial Intelligence,Business Model,Data Competitiveness,Scalp Analysis System, |
出版年 : | 2024 |
學位: | 碩士 |
摘要: | AI圖像辨識技術在美髮沙龍產業中的應用正成為一個商業模式創新的重要方向。隨著科技的進步和消費者對個性化服務的需求增加,美髮沙龍業面臨著許多挑戰和機會。AI圖像辨識技術可以幫助美髮沙龍業提供更準確和個性化的頭皮護理建議,從而提高顧客滿意度並增加業務收益。本研究將探討AI圖像辨識在美髮沙龍產業中的商業模式,包括技術應用、數據收集和分析、市場定位和價值創造等方面的創新。通過分析現有商業模式所遇到的困難,我們提出一個基於AI圖像辨識的商業模式和創新框架,以幫助美髮沙龍業者在競爭激烈的市場中取得優勢和成長機會。
本研究我們結合產醫學各方面的能力,運用學界AI圖像辨識將專業的醫學知識訓練AI人工智慧模型來協助美髮沙龍產業在頭皮養護上面的服務,解決其在頭皮知識方面的缺乏,進而創造美髮沙龍產業新的商業模式,透過研究的過程我們也深刻地體悟到擁有大數據資料不代表就具備足夠的競爭力,數據競爭力是否能夠有效的充分表現在商業模式上,還必須充分的理解自身在大數據蒐集上「數據本身的競爭力」以及「組織應用數據能力的競爭力」,進一步針對數據競爭力的不足與可能面臨的問題,做出適當的因應與對策,以確保自身在應用數據的決策過程中所形成的商業模式能夠達成。 在研究的最後我們總結得到下面幾個結論: 1.透過AI技術的應用可以整合不同產業的價值 2.利用AI技術圖像辨識可以創造新的機會與商業模式 3.擁有龐大的數據量,並不意味著就具有強大的數據競爭力 4.數據本身是否具有競爭力與數據的特性有一定的關係 5.組織本身的條件與資源,牽動著組織是否能夠運用數據而創造出競爭力 6.研究數據競爭力可以延伸創新的機會,增加創造產業價值的可能 The application of AI image recognition technology in the hair salon industry is becoming an important area for business model innovation. With advancements in technology and increasing consumer demand for personalized services, the hair salon industry faces numerous challenges and opportunities. AI image recognition technology can assist salons in providing more effective and personalized scalp care recommendations, thereby enhancing customer satisfaction and increasing business revenue. This study aims to explore the business models of AI image recognition in the hair salon industry, including technological applications, data collection and analysis, market positioning, and value creation. By analyzing existing business models and successful cases, we propose an AI image recognition-based business model and innovation framework to help hair salon service providers gain a competitive edge and seize growth opportunities in a highly competitive market. In this study, we combine the capabilities from various aspects of the medical industry and utilize AI image recognition from academia to train AI models with specialized medical knowledge to assist the hair salon industry in scalp care services, addressing their lack of expertise in scalp health. This, in turn, creates a new business model for the hair salon industry. Through the research process, we have also come to a profound realization that possessing a large volume of data does not necessarily equate to having high competitiveness. The competitiveness of data must also effectively manifest in the business model, necessitating a thorough understanding of both the “competitiveness of the data itself” and the “competitiveness of the organization in utilizing data.” After comprehending their data competitiveness, organizations must further address deficiencies and potential challenges in data competitiveness and develop appropriate strategies and countermeasures to ensure the effectiveness of the business models formed through data utilization in decision-making processes. In conclusion, our research has yielded the following findings: 1.Applications of AI technologies can support the integration of the values across different industries. 2.AI-based image recognition technologies can help create new opportunities and business models. 3.Having a large amount of data collection does not guarantee high data competitiveness. 4.The competitiveness of data itself is related to the properties of data. 5.The conditions and resources of the organization influence whether the organization can utilize data to create competitiveness. 6.Researching data competitiveness can extend innovative opportunities and increase the potential to create industry values. |
URI: | http://tdr.lib.ntu.edu.tw/jspui/handle/123456789/94641 |
DOI: | 10.6342/NTU202403764 |
全文授權: | 同意授權(全球公開) |
顯示於系所單位: | 資訊管理組 |
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