An acceptance model for smart watches Implications for the adoption of future wearable technology

被引:340
作者
Kim, Ki Joon [1 ]
Shin, Dong-Hee [1 ]
机构
[1] Sungkyunkwan Univ, Dept Interact Sci, Seoul, South Korea
关键词
Integrated acceptance model; Smart watch; Wearable technology; USER ACCEPTANCE; INFORMATION-TECHNOLOGY; INTEGRATED MODEL; FIT INDEXES; SERVICES; DETERMINANTS; SMARTPHONES; UTILITARIAN; VOIP;
D O I
10.1108/IntR-05-2014-0126
中图分类号
F [经济];
学科分类号
02 ;
摘要
Purpose - The purpose of this paper is to identify the key psychological determinants of smart watch adoption (i.e. affective quality (AQ), relative advantage (RA), mobility (MB), availability (AV), subcultural appeal) and develops an extended technology acceptance model (TAM) that integrates the findings into the original TAM constructs. Design/methodology/approach - An online survey assessed the proposed psychological determinants of smart watch adoption. Confirmatory factor analysis (CFA) and structural equation modeling (SEM) were conducted on collected data (n = 363) using the AMOS 22 statistical software. The reliability and validity of the measurement assessing the proposed factor structure were examined via CFA, while the strength and direction of the hypothesized causal paths among the constructs were analyzed via SEM. Findings - The AQ and RA of smart watches were found to be associated with perceived usefulness, while the sense of MB and AV induced by smart watches led to a greater perceived ease of the technology's use. The results also indicated that the devices' subcultural appeal and cost were notable antecedents of user attitude (AT) and intention to use, respectively. Originality/value - Though smart watches are becoming increasingly popular, empirical studies on user perceptions of and ATs toward - them remain preliminary. This paper is one of the first scholarly attempts at a systematic prediction of smart watch usage, with implications for the adoption of future wearable technology.
引用
收藏
页码:527 / 541
页数:15
相关论文
共 53 条
  • [11] GILLICK K, 2000, SMART CARD FOR ANN M
  • [12] Horton M, 2012, PSYCHNOLOGY J, V10, P73
  • [13] Cutoff Criteria for Fit Indexes in Covariance Structure Analysis: Conventional Criteria Versus New Alternatives
    Hu, Li-tze
    Bentler, Peter M.
    [J]. STRUCTURAL EQUATION MODELING-A MULTIDISCIPLINARY JOURNAL, 1999, 6 (01) : 1 - 55
  • [14] Elucidating user behavior of mobile learning - A perspective of the extended technology acceptance model
    Huang, Jen-Hung
    Lin, Yu-Ru
    Chuang, Shu-Ting
    [J]. ELECTRONIC LIBRARY, 2007, 25 (05) : 585 - 598
  • [15] Hung S.Y., 2003, Electronic Commerce Research Applications, V2, P42, DOI DOI 10.1016/S1567-4223(03)00008-5
  • [16] Race, gender, and information technology use: The new digital divide
    Jackson, Linda A.
    Zhao, Yong
    Kolenic, Anthony, III
    Fitzgerald, Hiram E.
    Harold, Rena
    Von Eye, Alexander
    [J]. CYBERPSYCHOLOGY & BEHAVIOR, 2008, 11 (04): : 437 - 442
  • [17] Exploring Koreans' smartphone usage: An integrated model of the technology acceptance model and uses and gratifications theory
    Joo, Jihyuk
    Sang, Yoonmo
    [J]. COMPUTERS IN HUMAN BEHAVIOR, 2013, 29 (06) : 2512 - 2518
  • [18] Factors affecting e-book reader awareness, interest, and intention to use
    Jung, Jaemin
    Chan-Olmsted, Sylvia
    Park, Bellnine
    Kim, Youngju
    [J]. NEW MEDIA & SOCIETY, 2012, 14 (02) : 204 - 224
  • [19] Information technology adoption across time: A cross-sectional comparison of pre-adoption and post-adoption beliefs
    Karahanna, E
    Straub, DW
    Chervany, NL
    [J]. MIS QUARTERLY, 1999, 23 (02) : 183 - 213
  • [20] Kelly H., 2014, CNN, P1