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User Experience and the Multi-Stage Adoption of Mobile Apps

원문정보

Ambrose Kim, Kyoung-jae Kim

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초록

영어

The adoption of technology has always been of interest to academicians and practitioners of the field of Management Information System. This is so because without proper and adequate adoption, technology-no matter how beneficial or advanced it may be-will be of little value to users. Numerous researches, such as the researches of the Technology Acceptance Model (TAM) or the Unified Theory of Acceptance and Use of Technology (UTAUT), had been conducted to understand the human nature in association with the adoption or rejection of technologies that have bombarded the users. The coming of smart technologies (i.e., smart phones and devices), however, seems to have fundamentally changed the environment for adoption. The ubiquity combined with mobility of technology, especially when it comes to mobile apps, seem to make the old PC era of two-stage-pre and post-adoption models obsolete. A new model of adoption that identifies the determinants of technology acceptance and continuance is needed for the smart age. To this end, this paper undertakes an empirical study, by analyzing 229 users of Social Networking Service (SNS) mobile apps, to identify the role of user experience on the multi-stage adoption of technology, and provides results that User Experience (UX) plays the crucial role of bridging the separate stages of pre and post adoption of technologies. The paper concludes by providing practical implications of the new model as it relates to mobile apps and technologies, and recommendations for further studies to get a better understanding of technology adoption in the smart age.

목차

Abstract
 1. Introduction
 2. Theoretical Background
  2.1 Mobile Apps in the Smart Age
  2.2 Technology Adoption Models
  2.3 Social Influence and Word of Mouth
  2.4 User Experience (UX)
 3. Research Design and Model
  3.1 Research Model
  3.2 Operational Definition and Hypotheses
 4. Data Collection and Analysis
  4.1 Survey Questionnaire and Analysis Tool
  4.2 Descriptive Statistics of Samples
  4.3 Analysis of Measurement Model
  4.4 Analysis of Structural Model
 5. Conclusion
  5.1 Research Results and Implications
  5.2 Research Limitations and Recommendation
 References

저자정보

  • Ambrose Kim Department of MIS, Graduate School, Dongguk University-Seoul
  • Kyoung-jae Kim Professor of MIS, Business School, Dongguk University-Seoul

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