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研究生:蔡季晨
研究生(外文):Tsai, Chi-Chen
論文名稱:投信資金募集以AI人工智慧模式之研究
論文名稱(外文):Research of AI Model of Trust Fund Raising
指導教授:王偉權王偉權引用關係洪瑞成洪瑞成引用關係
指導教授(外文):WANG, WEI-CHUANHUNG, JUI-CHENG
口試委員:洪瑞成劉德芝楊達凱王偉權
口試委員(外文):HUNG, JUI-CHENGLIU, DE-CHIHYANG, TA-KAIWANG, WEI-CHUAN
口試日期:2019-06-21
學位類別:碩士
校院名稱:中國文化大學
系所名稱:企業實務管理數位碩士在職專班
學門:商業及管理學門
學類:企業管理學類
論文種類:學術論文
論文出版年:2019
畢業學年度:107
語文別:中文
論文頁數:82
中文關鍵詞:資產管理產業人工智慧任務科技適配理論知識管理系統期望確認模型理論
外文關鍵詞:asset management industryartificial intelligencetask-technology fit theoryknowledge management systemexpectation confirmation model theory
相關次數:
  • 被引用被引用:2
  • 點閱點閱:472
  • 評分評分:
  • 下載下載:50
  • 收藏至我的研究室書目清單書目收藏:2
  近十年來金融環境革命性的改變,導致對資訊系統使用者之便利性及服務內容的質變。投信業募集基金運用AI架構,打造智慧募資模式,達到公司的目標,將成為重要的議題。
  本研究以任務-科技配適模型為基礎,探討科技特性滿足支援的任務特性的適配度時,對於績效成正向的成長。再運用知識管理系統探討歷史的募集資金模式,將成功的知識管理透過AI得以延續,提高資訊系統使用者滿意度,以達到公司所期望的募集資金目標,使基金規模之增長績效,持續成長。
  過往文獻未將三項理論關係做結合,本研究結合科技適配理論、知識管理系統、期望確認理論來探討投信募集資金運用AI模式研究,並透過問卷調查法為研究方法,並以結構方程模式(SEM)作為統計分析。
  研究結論為投信業募集資金AI模式,以此研究對投信業產業提出主要之策略方向,並將研究成果概念可以應用於台灣政府四大基金。

  The revolutionary changes in the financial environment in the past decade have led to changes in the convenience of information system users and the quality of the services. The investment industry fund raising fund uses the AI framework to create a smart fundraising model for wireless network applications.
  The use of AI framework by the investment fund raising foundation to create a smart model of fundraising for wireless network applications to meet the goals set by the executives of the company will become an important issue. This study is based on the task-technical fitness model and explores the positive growth of performance when the technical characteristics meet the goodness of fit of the task characteristics it supports.
  Then, using the knowledge management system to investigate the historical fundraising model for wireless network applications, and continue the successful knowledge management through AI, improve the user satisfaction of the information system, to achieve the company's desired fundraising goal, so that the growing performance of the fund can continue. The past literature does not combine the three theoretical relationships. This study combines the Task Technology Fit theory, the Knowledge Management System, and the Expectation Confirmation theory to explore the use of the deep learning model for the asset management industry. The key factors for the successful funds raised from the various enterprises are extracted. Through statistical analysis, these serve as a reference for relevant decision-making, increase the performance of raised funds and the efficiency of corporate organization, and to achieve the desired goal of raised funds set by the management. The subjects of this study are those who have not used the deep learning model structure and the users of the AI system, and use the online questionnaire to conduct convenient sampling, using questionnaires and SEM structural equation models for analysis.
  The research result is to construct the deep learning model of fund-raising in the asset management industry , and proposes the main strategic direction for the asset management industry and the concept of the research results can be applied to the four major funds of the Taiwan government.

內容目錄
中文摘要........................iii
英文摘要........................iv
誌謝辭.........................vi
內容目錄........................vii
表目錄.........................ix
圖目錄.........................x
第一章  緒論.....................1
第一節  研究背景.................1
第二節  研究動機.................3
第三節  研究目的.................6
第四節  研究流程與章節架構............8
第五節  研究範圍................10
第二章  文獻探討..................11
第一節  投信產業................11
第二節  人工智慧................15
第三節  任務科技適配理論............17
第四節  知識管理系統..............23
第五節  期望確認理論..............31
第六節  知識分享................37
第三章  研究方法..................39
第一節  研究架構................39
第二節  研究對象與問卷設計...........42
第三節  研究分析方法..............46
第四章  研究分析結果................48
第一節  敘述統計之分析..............48
第二節  測量模式之分析..............50
第三節  結構模式之分析.............53
第五章  研究結論與建議...............57
第一節  研究結論................57
第二節  研究建議................60
第三節  研究限制................61
參考文獻.......................62
附錄 問卷......................77


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