Acceptance of mobile technology by older adults

Kim, Sun‐Young; Gajos, Krzysztof Z.; Müller, Michael; Grosz, Barbara J.

doi:10.1145/2935334.2935380

Cited by 63 publications

(48 citation statements)

References 30 publications

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“…[19]), factors of interest for this work were trust and distrust (Round 1); Technology Acceptance Model (TAM) factors including perceived usefulness, perceived ease of use, and perceived risk (Round 2); and disruptiveness to practices of daily living [10] (cf. "conversion readiness" [35]) (Round 3). The research for all three focus groups received ethics approval from Lancaster University.…”

Section: Methodsmentioning

confidence: 99%

“…It is possible that by not collecting data pertaining to other factors that may be influencing adoption-e.g. subjective norms/social influence and facilitating conditions [64,78]; experience with technology [2,8]; gender and health [54]; self-efficacy and peer support [35]-we missed key explanatory dynamics. And yet despite having initially intended to contribute towards efforts to enhance the TAM model with factors such as risk and trust [33,65], and having anticipated suggesting the addition of perceived beneficiaries as a relevant factor, we have come to doubt the explanatory power of TAM for older adults specifically.…”

Section: Appropriateness and Validity Of Tammentioning

confidence: 99%

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Older Adults’ Deployment of ‘Distrust’

Knowles

Hanson

2018

ACM Trans. Comput.-Hum. Interact.

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Older adults frequently deploy the concept of distrust when discussing digital technologies, and it is tempting to assume that distrust is largely responsible for the reduced uptake by older adults witnessed in the latest surveys of technology use. To help understand the impact of distrust on adoption behavior, we conducted focus groups with older adults exploring how, in what circumstances, and to what effect older adults articulate distrust in digital technologies. Our findings indicate that distrust is not especially relevant to older adults' practical decision making around technology (non-)use. The older adults in our study used the language of distrust to open up discussions around digital technologies to larger issues related to values. This suggests that looking to distrust as a predictor of non-use (e.g. in Technology Acceptance Model studies) may be uniquely unhelpful in the case of older adults, as it narrows the discussion of technology acceptance and trust to interactional issues, when their use of distrust pertains to much wider concerns. Likewise, technology adoption should not be viewed as indicative of trust or an endorsement of technology acceptability. Older adults using-while-distrusting offers important insights into how to design truly acceptable digital technologies.

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Section: Methodsmentioning

confidence: 99%

Section: Appropriateness and Validity Of Tammentioning

confidence: 99%

Older Adults’ Deployment of ‘Distrust’

Knowles

Hanson

2018

ACM Trans. Comput.-Hum. Interact.

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“…Several studies dedicated to navigation aids and to older people highlight some dimensions that particularly shape the user experience. Thus, among the pragmatic qualities that are important for navigation aids stand their usability, the accuracy of the GPS, and their ease of learning [49,50], especially among older people [51]. Nonpragmatic qualities, such as aesthetics, trustworthiness, discretion, and autonomy, are relevant too, especially among older people [52,53].…”

Section: User Experience With Navigation Aidsmentioning

confidence: 99%

Using Sensory Wearable Devices to Navigate the City: Effectiveness and User Experience in Older Pedestrians

Montuwy

Cahour

Dommès³

2019

MTI

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Preserving older pedestrians’ navigation skills in urban environments is a challenge for maintaining their quality of life. However, the maps that are usually used by older pedestrians might be unsuitable to their specificities and the existing digital aids do not consider older people’s perceptual and cognitive declines or user experience. This study presents a rich description of the navigation experience of older pedestrians either with a visual (augmented reality glasses), auditory (bone conduction headphones), or a visual and haptic (smartwatch) wearable device adapted to age-related declines. These wearable devices are compared to the navigation aid older people usually use when navigating the city (their own digital or paper map). The study, with 18 participants, measured the navigation performance and captured detailed descriptions of the users’ experience using interviews. We highlight three main phenomena which impact the quality of the user experience with the four aids: (1) the shifts in attention over time, (2) the understanding of the situation over time, and (3) the emergence of affective and aesthetic feelings over time. These findings add a new understanding of the specificities of navigation experience by older people and are discussed in terms of design recommendations for navigation devices.

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“…This model is integral in our discussion of technology acceptance. This model have been doing great in predicting and explaining technology acceptance in a wide range of area not only in IoT, but from Cloud Computing (Eltayeb & Dawson, 2016), to mobile technology (Kim, Gajos, Muller, & Grosz, 2016) and e-learning platform (Al-Azawei, Parslow, & Lundqvist, 2016), and even health trackers (Prayoga & Abraham, 2016). In this chapter, we are going to talk about what the model has to offer, and all possible frequently used factors to compliment TAM for a better understanding of IoT Acceptance.…”

Section: The Variablesmentioning

confidence: 99%

Technopsychology of IoT Optimization in the Business World

Prayoga

Abraham

2017

The Internet of Things in the Modern Business Environment

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There are at least two complementary levels when we are talking about the Internet of Things. The first (back) end come from the Big Data companies that mine and analyze every log of activities through every device that are attached to the second (front) end, i.e. the many aspects of our lives. However, what keeps this wheel of innovation going is actually the front end user. Technology, however improved and innovative, will not fulfill its full potential if said users do not adopt and accept it as part of their lives. They must be willing to work with the technology−sold as way to ease and improve lives−for the machine to work and be meaningful. By then the Big Data companies can gather information about what users want and how they behave to grasp a better understanding and make better decisions about next technology improvement. Users' acceptance and decisions to appropriate shape how Big Data company works and innovate. Acceptance and Appropriation then become the two of the most important area to explore in the field of IoT optimization in the business world.cognitive decision support approach. Journal of Computers, 7(7), 1574-1582. http://dx.doi.org/10.4304/jcp.7.7.1574-1582 KEY TERMS AND DEFINITIONSAppropriation: The use of a technology that is not as intended by the developers or the designers−does not necessarily mean positive or negative.Artificial Intelligence (AI): High performing, extensive and versatile cognitive system made by human to automate and let machines learn. Cyber-resilience:The ability of a person or organization to withstand the pressure of cyberrelated adversaries.Data Economy: An emerging economy trend that is data-driven. Data, especially IoT-generated, is seen as the driving force behind the dynamic interaction between consumers and companies. Personality:The cognitive, affective, and behavior patterns, characteristics that is unique, can be influenced and dynamic that define an individual. Psychology:The scientific study of the mind and behavior. Technopsychology:The branch of Psychology that covers the convergence of and interaction between human and technology. ENDNOTES 1 The word 'I' refers to the authors About the Contributors In LeeisaprofessorintheSchoolofComputerSciencesintheCollegeofBusinessandTechnology atWesternIllinoisUniversity.HereceivedhisMBAfromtheUniversityofTexasatAustinandPh.D.

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Acceptance of mobile technology by older adults

Cited by 63 publications

References 30 publications

Older Adults’ Deployment of ‘Distrust’

Older Adults’ Deployment of ‘Distrust’

Using Sensory Wearable Devices to Navigate the City: Effectiveness and User Experience in Older Pedestrians

Technopsychology of IoT Optimization in the Business World

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