Masters Theses

Apurva Adapa

Keywords and Phrases

Adoption; Google glass; Laddering; Smart watch; Smart wearable devices; Wearable technology

Abstract

"This study aims to examine the factors and issues in adoption of smart wearable devices. Wearable devices have many functions to offer which make them very useful in our daily lives. However, factors influencing the adoption of these devices are not well understood. This research explores the inhibiting and contributing factors influencing the adoption of wearable devices by employing the laddering approach. Qualitative data were collected through in-depth interviews using the laddering technique in order to understand these factors. Wearable devices that were examined include the Smart Glass (Google Glass) and the Smart Watch (Sony Smart Watch 3). After the participants had the opportunity to try out these two devices, the factors that are most important to them in deciding whether to adopt or not to adopt these devices were laddered. The use of the laddering technique with the Means-End Chain approach not only offers a greater understanding of the factors influencing the adoption of wearable devices, but also reveal the relationships among these factors and any meaningful associations with self (i.e., the user). This research has advanced our understanding on the adoption of wearable devices and provide some insights into the key design criteria to better fit users' needs"--Abstract, page iii.

Advisor(s)

Nah, Fiona Fui-Hoon, 1966-

Committee Member(s)

Siau, Keng, 1964-
Hall, Richard H.

Department(s)

Business and Information Technology

Degree Name

M.S. in Information Science and Technology

Publisher

Missouri University of Science and Technology

Publication Date

Spring 2016

Pagination

vi, 43 pages

Note about bibliography

Includes bibliographical references (pages 41-42).

Rights

© 2016 Apurva Adapa, All rights reserved.

Document Type

Thesis - Open Access

File Type

text

Language

English

Subject Headings

Wearable technologyWearable computersHuman-computer interaction

Thesis Number

T 10862

Electronic OCLC #

952589771

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