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논문검색

Technology Adoption of InnovViz 2.0 : A Study of Mixed-Reality Visualization and Simulation System for Innovation Strategy with UTAUT Model

초록

영어

InnovVizwas designed and developed anew as avisualization and simulationtool to present innovation and strategy information. The InnovViz system employs two key types of technology, namely mixed reality (MR) and neural network (NN). An experiment was conducted to examine the usability, acceptance and possible adoption of this new system. Participants comprised 4 experts from 4 top performing entrepreneurial firms and 161 master degree students from 2 leading universities. The study used a modified UTAUT model and a cognition and perception model. The results revealed that when the InnovViz was introduced, the key drivers to adoption are Facilitating Conditions (FC) and Voluntary to Use (VOL). Adequate knowledge and sufficient resources were found to strongly affect FC construct. The expert"fs rating of a firm"fs innovation and performance was more congruent with senior students with a technology-background than with a finance and accounting-background. InnovViz was seen as providing complex information with an ease of use and usefulness for showing data and assessment. Among the three types of visuals depicted by InnovViz, experts rated their usefulness in descending order as follows: Cube, Tetrahedron and Saturn. Finally, experts found backward simulation to be slightly more useful for assessment than forward simulation.

목차

Abstract
 1. Introduction
 2. Mixed Reality (MR)
 3. Neural Network (NN) Simulation
 4. InnovViz 2.0
 5. Technology Adoption
 6. Cognition and Perception of Mixed Reality Visuals
 7. Research Method
  7.1 Study Constructs for Technology Adoption
  7.2 Study Constructs for Information Processing and Cognition
  7.3 Experiment Protocol
  7.4 Experimental Subjects
  7.5 Data Collection Instrument
 8. Analyses and Results
  8.1 Participant Characteristics
  8.2 Expert Characteristics
  8.3 Results of Technology Adoption
  8.4 Results of Cognition and Perception
 9. Discussion and Conclusion
  9.1 Limitation and Future Research
 Reference
 Author Profile

저자정보

  • Phannaphatr Savetpanuvong Technopreneurship and Innovation Management Program, Graduate School, Chulalongkorn University, Bangkok 10330, Thailand
  • Uthai Tanlamai Department of Accountancy, Chulalongkorn Business School, Chulalongkorn University, Bangkok 10330, Thailand
  • Chidchanok Lursinsap Department of Mathematics, Faculty of Science, Chulalongkorn University, Bangkok 10330, Thailand,
  • Pairote Leelaphattarakij LarnGear Technology, 99/25 Software Park Building 12thFl, Chaengwattana Rd, Nonthaburi 11120, Thailand
  • Wisit Kunarittipol LarnGear Technology, 99/25 Software Park Building 12thFl, Chaengwattana Rd, Nonthaburi 11120, Thailand
  • Supasate Choochaisri LarnGear Technology, 99/25 Software Park Building 12thFl, Chaengwattana Rd, Nonthaburi 11120, Thailand

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