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수학적 수요분석에 따른 메타버스 서비스의 혁신효과와 모방효과에 관한 연구
| DC Field | Value | Language |
|---|---|---|
| dc.contributor.advisor | 이상근 | - |
| dc.contributor.author | 변원기 | - |
| dc.date.accessioned | 2018-11-08T07:56:51Z | - |
| dc.date.available | 2018-11-08T07:56:51Z | - |
| dc.date.issued | 2011-02 | - |
| dc.identifier.other | 11528 | - |
| dc.identifier.uri | https://dspace.ajou.ac.kr/handle/2018.oak/8852 | - |
| dc.description | 학위논문(석사)--아주대학교 일반대학원 :경영정보학과,2011. 2 | - |
| dc.description.tableofcontents | 1. Introduction 1 2. Literature review 4 2.1 Types of Metaverse 4 2.2 Smart devices and social interactions 6 2.3 Technology Adoption measure 8 3. Research model 11 3.1 Hypotheses development 12 3.2 Data selection 15 3.2.1 Actual use of the technology, rather than the size of adoption 15 3.2.2 Intensity (Visit), rather than scope(Unique Visitor) 15 3.2.3 Secondlife.com for Virtual world 16 3.2.4 Maps.google.com for Mirror world 17 3.2.5 Twitter.com for Life logging 18 3.2.6 iPhone sales for Augmented reality 19 3.3 Adoption measure 20 3.4 Result 21 4. Discussion 27 5. Conclusion 29 5.1 Future research 30 Reference 32 Appendix 36 | - |
| dc.language.iso | eng | - |
| dc.publisher | The Graduate School, Ajou University | - |
| dc.rights | 아주대학교 논문은 저작권에 의해 보호받습니다. | - |
| dc.title | 수학적 수요분석에 따른 메타버스 서비스의 혁신효과와 모방효과에 관한 연구 | - |
| dc.type | Thesis | - |
| dc.contributor.affiliation | 아주대학교 일반대학원 | - |
| dc.contributor.department | 일반대학원 경영정보학과 | - |
| dc.date.awarded | 2011. 2 | - |
| dc.description.degree | Master | - |
| dc.identifier.localId | 569352 | - |
| dc.identifier.url | http://dcoll.ajou.ac.kr:9080/dcollection/jsp/common/DcLoOrgPer.jsp?sItemId=000000011528 | - |
| dc.subject.keyword | Metaverse | - |
| dc.subject.keyword | iPhone | - |
| dc.subject.keyword | Bass model | - |
| dc.description.alternativeAbstract | This study examines the innovation and imitation effects in Metaverse service adoption. We adopt Metaverseroadmap's classification plot to identify the world of Metaverse. These classifications are Augmented reality, Life logging, Mirror world, and Virtual world. All four dimensions have distinctive characteristics. As we expect smart devices play a significant role in triggering imitation effects, we employ the Bass model to analyze the time series data in the middle of which there has been iPhone's influx as an event. Result shows that these four dimensions yield different innovation and imitation coefficient values. Augmented reality has the higher innovation coefficient, P, while Life logging, and Mirror world represent the higher imitation coefficient, Q. Also Virtual world does not receive a statistically significant value. Implications are drawn to explain the differences. Mirror world’s imitation effects are based on network externalities, while Life logging’s imitation effects are caused by individuals’ interactions. Augmented reality’s innovation effects are explained by timing of the measurement. | - |
- Appears in Collections:
- Graduate School of Ajou University > Department of Management Information Systems > 3. Theses(Master)
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