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研究生: Diep Buu Linh
Diep Buu Linh
論文名稱: 理論與實踐的結合:軟體定價中的綜合因素及其對軟體擴散的影響研究
Bridging Theory and Practice: Examining Integrated Factors in Pricing Software and Their Influence on Software Popularity
指導教授: Karl Akbari
Karl Akbari
口試委員: 黃圭晟
Kyusung Hwang
Sungjun (Steven) Park
Sungjun (Steven) Park
學位類別: 碩士
Master
系所名稱: 管理學院 - 管理學院MBA
School of Management International (MBA)
論文出版年: 2023
畢業學年度: 112
語文別: 英文
論文頁數: 81
外文關鍵詞: algorithmic pricing, adaptive algorithm, learning algorithm, artificial intelligence, machine learning, dynamic pricing, personalized pricing, competitor-based pricing, location-based pricing
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  • This study delves into the an often-overlooked domain of algorithmic pricing - their underlying technologies. Through an analysis of real-world applications in pricing software, the study seeks to bridge the gap between theoretical understanding and industry practices, particularly in pricing approaches, data, and technological aspects. It explores how these factors are integrated in pricing software and their impact on the software's popularity.

    Table of contents Abstract IV Acknowledgments V Introduction 1 Literature Review 2 Algorithmic Pricing . .............................. 2 Traditional and AI-driven Algorithmic Pricing . ............ 3 Mechanisms of Algorithmic Pricing . .................. 3 Prominent Approaches of Algorithmic Pricing . ............... 4 Dynamic Pricing . ............................ 6 Personalized Pricing . .......................... 9 Alternative Approaches to Algorithmic Pricing . ............ 11 Technological Aspects of Algorithmic Pricing . ................ 14 Applications of Traditional Algorithmic Pricing . ........... 16 Applications of AI-drivenAl gorithmic Pricing . ............ 18 Methodology 28 Data Collection . ................................ 28 Product Characteristics . ........................ 28 Product Popularity . ........................... 32 Data Analysis . ................................. 34 Descriptive Analysis . .......................... 34 Cluster Analysis . ............................ 36 Product Popularity Analysis . ...................... 41 Results 42 Descriptive Analysis . ............................. 42 Pricing Approach . ............................ 42 Pricing Data . .............................. 42 Human Involvement . .......................... 43 Non-AI Function vs. AI/ML Function . ................ 45 AI Function vs. ML Function . ..................... 46 Cluster Analysis . ............................... 46 Pricing Approach . ............................ 47 Pricing Data . .............................. 48 Human Involvement . .......................... 51 Non-AI Function . ............................ 53 AI/ML Function . ............................ 55 Cluster Profiles . ............................. 59 Relationship between Clusters and Product Popularity . .......... 59 Discussion 63 Conclusion 69 Implications . .................................. 69 Limitations and FutureResearch . ...................... 70 References . ...................... 71

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