Publications

Detailed Information

Analysis of Technological Knowledge Flows in Business Model Innovation : 비즈니스 모델 혁신의 기술 지식 흐름 분석

DC Field Value Language
dc.contributor.advisor박용태-
dc.contributor.author안윤정-
dc.date.accessioned2017-10-27T16:36:22Z-
dc.date.available2017-10-27T16:36:22Z-
dc.date.issued2017-08-
dc.identifier.other000000145450-
dc.identifier.urihttps://hdl.handle.net/10371/136741-
dc.description학위논문 (박사)-- 서울대학교 대학원 공과대학 산업·조선공학부, 2017. 8. 박용태.-
dc.description.abstractWith the extensive applications of Information and Communication Technologies (ICTs) in development of new business models, the business model concept is becoming an important research topic in the field of innovation and technology management. The Internet has driven innovation and changes across the business landscape and opened the era of e-commerce. Since many of, or sometimes even entire, commercial activities thus can be conducted on the Internet platform, ICTs are becoming a key enabler in the creation of new business models. Companies are keen to leverage ICTs to develop specific methods underlying business models and seek protection for these new inventions under patent laws. These inventions, called business model patents or business method (BM) patents, refer to various commercial techniques that are usually based on digital or software-based technologies. The value of BM patents lies in the fact that these patents contain essential technological knowledge regarding business model innovation and also can facilitate business model development and innovation through knowledge flows. Despite the importance of technological knowledge flows in business model innovation, linkages between business model innovation/evolution, technology and knowledge flows are a rather rarely explored subject. The present literature does not pay much attention to the technological basis of business model innovation, flows of knowledge in business technologies or quantitative analysis of business model innovation. To fill this research gap, the overall objective of this work is to explore technological knowledge flows in business model innovation based on patent analysis.
This study consists of three research themes. The first research theme is to develop a structured approach to measure technological knowledge flows in business model innovation. The proposed approach integrates two complementary methods, the patent citation analysis and text mining technique. The empirical study applies the proposed approach to measure knowledge flows through BM patents and reveals that BM patents actively participate in stimulating knowledge flows in business model innovation.
The second research theme is to identify patterns of technological knowledge flows in business model innovation. This study applies a dynamic approach to capture time-varying processes of knowledge flows in BM patents. A Hidden Markov Model, patent citation analysis and clustering technique are used to identify major temporal patterns of knowledge flows in BM patents.
The third research theme discusses positions or roles of BM patents regarding knowledge flows in business model innovation. This study propose a systematic framework directed at investigating different roles of BM patents that facilitate knowledge flows for innovations in social commerce. The framework mainly uses several citation-based indicators to identify core BMs and specifies their roles according to knowledge flow patterns.
This study extends overall understanding of the technological aspect of business model innovation by linking the concept of business model innovation with technological development and knowledge flows and providing systematic ways to utilize patent citation analysis and other effective techniques.
-
dc.description.tableofcontentsChapter 1. Introduction 1
1.1. Background and motivation 1
1.2. Research objectives 4
1.3. Scope and framework 5
1.4. Thesis outline 7
Chapter 2. Literature Review 10
2.1. Business model innovation and technology management 10
2.2. Knowledge flows 13
2.3. Business method (BM) patents and patent citation analysis 15
Chapter 3. Measurement of Knowledge Flows 17
3.1. Introduction 17
3.2. Research Proposed approach: integrating patent citation analysis and text mining 22
3.2.1. Overall research process 22
3.2.2. Integrated approach by combining patent citation analysis and text mining 24
3.2.3. Similarity measure 26
3.3. Case study: postage metering system 30
3.3.1. Data collection 30
3.3.2. Construction and integration of matrices 32
3.3.3. Patterns of knowledge flow 35
3.3.3.1. High KU-High KD 38
3.3.3.2. High KU-Low KD 38
3.3.3.3. Low KU-High KD 38
3.3.4. Classification of knowledge flow drivers 39
3.3.4.1. Knowledge utilizing group 41
3.3.4.2. Knowledge disseminating group 41
3.3.4.3. Knowledge utilizing/ disseminating group 42
3.4. Implication and conclusion 42
Chapter 4. Identification of Knowledge Flow Patterns 46
4.1. Introduction 46
4.2. Hidden Markov Models 50
4.3. Proposed approach 53
4.3.1. Data 53
4.3.2. Research process 54
4.3.2.1. Select patent citations as a proxy for knowledge flows 54
4.3.2.2. Measure time series citation data for BM subclasses 55
4.3.2.3. Construct a HMM and generate sequences of knowledge flow states 56
4.3.2.4. Cluster knowledge flow state sequences to identify major patterns 59
4.4. Case study 61
4.4.1. Data 61
4.4.2. Analysis and results 61
4.4.3. Discussions 70
4.4.3.1. Major patterns of knowledge flows 70
4.4.3.2. Methodological implications and extensions 74
4.5. Conclusions 75
Chapter 5. Investigation of Knowledge Transferors 79
5.1. Introduction 79
5.2. Social commerce 81
5.3. Research framework 84
5.3.1. Overall research framework 84
5.3.2. Detailed process 85
5.3.2.1. Data collection 85
5.3.2.2. Classification of BMs in social commerce 87
5.3.2.3. Identification of core BMs 88
5.4. Empirical analysis and results 91
5.4.1. Data collection 92
5.4.2. Classification of BMs in social commerce 92
5.4.3. Identification of core BMs 98
5.4.4. Interpretation of results 101
5.5. Conclusion 104
Chapter 6. Conclusion 107
6.1. Summary and contributions 107
6.2. Limitations and future research 110
Bibliography 112
Appendix 124
Appendix A. Social commerce patents 124
Appendix B. Social commerce patent clusters 128
Appendix C. Indicator values for clusters 129
초 록 131
-
dc.formatapplication/pdf-
dc.format.extent4002633 bytes-
dc.format.mediumapplication/pdf-
dc.language.isoen-
dc.publisher서울대학교 대학원-
dc.subjectBusiness model innovation-
dc.subjectKnowledge flows-
dc.subjectBusiness technology-
dc.subjectBusiness method patents-
dc.subjectPatent citation analysis-
dc.subject.ddc623.8-
dc.titleAnalysis of Technological Knowledge Flows in Business Model Innovation-
dc.title.alternative비즈니스 모델 혁신의 기술 지식 흐름 분석-
dc.typeThesis-
dc.description.degreeDoctor-
dc.contributor.affiliation공과대학 산업·조선공학부-
dc.date.awarded2017-08-
Appears in Collections:
Files in This Item:

Altmetrics

Item View & Download Count

  • mendeley

Items in S-Space are protected by copyright, with all rights reserved, unless otherwise indicated.

Share