Acceptance of Mobile Technology in Hedonic Scenarios

Abstract

This paper presents a novel acceptance model for scenarios in which people make use of mobile devices for leisure purposes. The use of mobile devices has such a dominant leisure component that user attitudes towards mobile adoption are strongly determined. Since hedonic aspects play a key role in mobile adoption, they are introduced through the constructs in the proposed Technology Acceptance Model (TAM). To validate the TAM, 79 teenagers took part in an outdoor event that aimed to foster creativity through the use of a mobile phone. Different features of the mobile phone were used by the teenagers to conduct interviews, communicate with peers, and orient themselves using the GPS, among other applications. The proposed TAM yielded successful results since a Principal Components Analysis (PCA) revealed that the constructs Perceived Usefulness, Perceived Ease of Use and Perceived Enjoyment determined Behavioural Intention, exhibiting a high variance of 60.2%. In addition, the explanatory power of the model reached R 2 =61%, which is considered strong.

Technology Acceptance Evaluation by Deaf Students Considering the Inclusive Education Context

“…These findings can be seen as a shed of light over a path that can be followed as evidence. The literature review also confirms some of the findings, showing concrete results of the relationship between constructs used in TAM4IE, such as Facilitating conditions with User behavior [32], Perceived usefulness with Behavioral intention [8] and Subjective perception with Perceived usefulness [1,34].…”

“…1. Subjective perception (SP) construct was shaped by literature on user experience aspects in technology acceptance models [10,11,12,22], on works that proposed technology acceptance models while taking hedonic quality into account [1,9,33,34], and on those papers that were essential to create Emotion-LIBRAS 1 . Emotion-LIBRAS is an emotional user experience evaluation instrument for use by deaf participants, which was proposed and tested in previous works [25] and is shown in Fig.…”

Individual Differences in Frustration and Performance with Online Shopping Activities

“…Following completion of the shopping task, participants were directed to report their post-task mood with the BMIS (Mayer & Gaschke, 1988) for comparison to pre-task mood, complete the RFDT scale (Hadlington and Scase, 2018), TAM scale (Abad et al, 2010;Venkatesh and Davis, 1996;Venkatesh et al, 2012), BIG Five Inventory (BFI; John and Srivastava, 1999), subjective technology experience (Giacomini, Lyle III, and Wynn, 2012), and finally, demographics.…”

Examining frustration and performance when priming user expectations and providing a technology malfunction

“…Scores for all 26 items were summed, such that higher scores indicated more maladaptive responses and lower scores indicated more adaptive responses to failures with technology. The third section assessed a Technology Acceptance Model (TAM) with five perceived usefulness items adapted from Abad, Diaz, and Vigo (2010), six perceived ease of use items adapted from Venkatesh and Davis (1996) and Abad et al (2010), and six perceived enjoyment items adapted from Venkatesh, Thong, and Xu (2012) and Abad et al (2010). All responses for the adapted TAM were scored on a 7-point Likert scale, where 1=strongly disagree and 7=strongly agree.…”