Wearable XR-technology: literature review, conceptual framework and future research directions

Chuah, Stephanie Hui-Wen

doi:10.1504/ijtmkt.2019.104586

Cited by 40 publications

(22 citation statements)

References 142 publications

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“…Moreover, concerns regarding unauthorized access to one's health data and photos generated using the cameras integrated into the devices lower the likelihood of consenting to treatments with MR headsets [14]. This skepticism confirms studies from the consumer sector [15], for instance, by revealing that privacy concerns significantly reduce MR acceptance [24].…”

Section: Figure 1 Ppe Using Vsi Pe [7]mentioning

confidence: 66%

“…Moreover, a crossover trial with elderly patients by Rohrbach et al [11] revealed that 30% of the control group tended to be reluctant toward wearing MR glasses due to their novelty and the lack of wearing comfort. In line with these observations, Chuah [15] recently called for illuminating user resistance to MR technologies by employing configurational approaches to provide researchers and practitioners with insights into the factors that explain the lack of acceptance of MR glasses.…”

Section: Introductionmentioning

confidence: 99%

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The Force of Habit: Examining the Status Quo Bias for Using Mixed Reality in Patient Education

Anton¹,

Schuir²,

Teuteberg³

2022

Proceedings of the Annual Hawaii International Conference on System Sciences

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Using mixed reality (MR) glasses for preoperative patient education (PPE) can help patients understand the purpose and risks of surgical procedures through informative visualizations. However, patients tend to be critical regarding the use of MR glasses in healthcare and often prefer the status quo of healthcare services provided. This study explores the resistance to MR technologies in PPE through the lens of the status quo bias theory by surveying n = 171 participants. We conducted a fuzzy set qualitative comparative analysis revealing configurations that provide a typological understanding of patient resistance. This allows healthcare stakeholders to take more targeted interventions to promote MR adoption. Notably, the results indicate that healthcare providers need to be transparent in communicating the benefits and drawbacks of using MR, as uncertainty costs are the main driver of resistance to MR glasses in PPE.

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Section: Figure 1 Ppe Using Vsi Pe [7]mentioning

confidence: 66%

Section: Introductionmentioning

confidence: 99%

The Force of Habit: Examining the Status Quo Bias for Using Mixed Reality in Patient Education

Anton¹,

Schuir²,

Teuteberg³

2022

Proceedings of the Annual Hawaii International Conference on System Sciences

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“…In addition, IoT can be used to discrimination against certain individuals when prioritizing people for health-care treatment by pinpointing good and bad citizens based on behavioral data collected by IoT (Wright et al , 2014). These adverse consequences might hinder the wider acceptance of IR 4.0 technologies (Chuah, 2019).…”

Section: Health Carementioning

confidence: 99%

Opportunities of and threats to consumer well-being in the age of Fourth Industrial Revolution (IR 4.0) technologies

Boninsegni

Roy

Bakpayev

et al. 2021

DPRG

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Purpose Fourth Industrial Revolution (IR 4.0) technologies have strong potential to affect consumer well-being, positively or negatively, so the current paper aims to review potential opportunities and threats that these technologies represent for consumers in several core economic sectors: health care, education, financial services, manufacturing and retailing. Design/methodology/approach This paper proposes a conceptual framework for how IR 4.0 technologies affect consumer well-being in five representative sectors: health care, education, financial services, manufacturing and retailing. The authors argue that the potential transformations of these specific sectors, facilitated by these technologies, may have profound effects on consumer well-being, with urgent public policy implications. Findings Emerging technologies, such as artificial intelligence, robotics, the Internet of Things, three-dimensional printing, machine learning and blockchain, provide customers with novel approaches toward decisions regarding health, education, finances and other fundamental parts of their lives. The organizations that provide these services, such as hospitals, universities and banks, actively adopt the innovations offered by IR 4.0. These evolving and disruptive technologies thus are changing reality for consumers and providers. Originality/value This paper proposes some novel public policy implications of IR 4.0 technologies for consumer well-being, and it outlines further research directions that can enhance understanding of relevant technologies and the consequences of their use for society.

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“…In spite of the vast growth of XR, consumer acceptance is still limited and academic research on such technology and their applications are extremely restricted (Bonetti et al , 2018). For instance, companies and researchers who are studying the use of wearable devices in tourism (Chuah, 2019), demonstrated that little attention has been paid to using predictive models for XR wearable technology acceptance which is a new technology (Herz and Rauschnabel, 2019).…”

Section: Literature Reviewmentioning

confidence: 99%

“…Another issue is that previous studies on predictive models have not focussed on dark side of technology accpetance and less is known about why users resist to technology which is a major reason for the failures of new IS implementation (Chuah, 2019). For instance, Suh and Prophet (2018), have highlighted the negative parts of technology acceptance models such as motion sickness, physical discomfort, cognitive overload and distracted attrition, which could increase user stress levels.…”

Section: Literature Reviewmentioning

confidence: 99%

The evolution of predictive models and tourism

Gharibi

2020

JTF

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Purpose This study aims to investigate the predictive technology acceptance models and their evolution in the tourism context. These predictive models make a knowledgeable decision about the possibility of future outcomes by analysing data. As futurists are interested in making a prediction about the likelihood of different behaviours over time, researchers of these predictive models have focussed on behaviour and predicting the intentions of users. This study proposes to demonstrate the revolution of these models and how are changed overtime. It also indicates the role of them in future studies. Design/methodology/approach By reviewing the predictive models and literature, this study looks in-depth in the process of alteration of these models. Findings This study explores the reasons of the evolution of predictive models and how they are changed. It shed light on the role of predictive models in future research and will suggest new directions for forthcoming studies. Research limitations/implications One of the main limitations of this study is that as the world is currently struggling with COVID-19 and predictability of these models will be changed. As the future is disruptive, it cannot be concluded that how these models will be altered in future. Practical implications Role of predictive behavioural models of tourists is fundamentally crucial in assessing the performance of planners and marketers of tourism services in the future. It will also vastly helps the successful development of tourism sectors, and it has practical value for all tourism stakeholders. Originality/value Few studies have focussed on the evaluation of these models and their role in future research.

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Wearable XR-technology: literature review, conceptual framework and future research directions

Cited by 40 publications

References 142 publications

The Force of Habit: Examining the Status Quo Bias for Using Mixed Reality in Patient Education

The Force of Habit: Examining the Status Quo Bias for Using Mixed Reality in Patient Education

Opportunities of and threats to consumer well-being in the age of Fourth Industrial Revolution (IR 4.0) technologies

The evolution of predictive models and tourism

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