Hybrid analysis for understanding contact tracing apps adoption

Duan, Sophia Xiaoxia; Deng, Hepu

doi:10.1108/imds-12-2020-0697

Cited by 55 publications

(57 citation statements)

References 30 publications

(128 reference statements)

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“… Chan and Saqib (2021) (on French, Australian and US populations) Xs: Social influence, facilitating condition, effort expectancy, performance expectancy, perceived privacy risk Mediator: Perceived value of information disclosure Y: Adoption intention The study shows that effort expectancy, perceived value of information disclosure and social influence are critical for adopting contact-tracing apps. Duan and Deng (2021) (on an Australian population) Time 1: Xs: Social influence, reciprocal benefits, perceived health benefits, Privacy concerns Ys: Adoption intentions, willingness to rely Time 2: Xs: Social influence, reciprocal benefits, perceived health benefits, privacy concerns Mediators: Adoption intentions, willingness to rely Y: Usage intentions Reciprocal benefits positively influence technology acceptance. Time is an important factor during a crisis, and it will influence citizen acceptance of the app.…”

Section: Theoretical Frameworkmentioning

confidence: 99%

The psychological reassurance effect of mobile tracing apps in Covid-19 Era

Kurtaliqi

Zaman

Sohier

2022

Computers in Human Behavior

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As part of their public health policies, most countries have launched mobile tracing applications (apps) to reduce the spread of the COVID-19 virus and reassure their citizens. To the best of our knowledge, no study has explored the importance of ‘well-being’ and ‘trust in the future’ in the context of digital contact-tracing apps. This is an important gap, especially given the importance of citizens' acceptance of a mobile tracing app and its role in reassuring citizens. Therefore, we study the French government's tracing app—StopCovid—as experienced by a sample of 832 participants from France. The results establish strong links between perceived value and trust in government, well-being, and trust in the future, which are considered the key features of the reassurance effect in a pandemic context. In addition, a multigroup analysis (MGA) allows us to compare the effect of several moderators on the overall model, such as the users versus nonusers of tracking apps or infected versus noninfected with COVID-19. The study provides practical implications by highlighting how governments should deploy mobile tracing apps to contribute to public health and reassure their citizens during the pandemic.

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Section: Theoretical Frameworkmentioning

confidence: 99%

The psychological reassurance effect of mobile tracing apps in Covid-19 Era

Kurtaliqi

Zaman

Sohier

2022

Computers in Human Behavior

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“… Bui Thanh Khoa (2020) [ 109 ] Mobile banking services Perceived credibility Information interest Perceived control Privacy concern Perceived vulnerability Perceived value It was found that all the constructs of perceived benefits and perceived costs have a remarkable effect on perceived value in the mobile banking services context. Duan and Deng, H. (2021) [ 110 ] Contact tracing apps Performance expectancy Perceived privacy risk Perceived value of information disclosure The analysis result confirmed that performance expectancy and perceived privacy risks are indirectly significant on the adoption through the influence of perceived value of information disclosure. Zhu et al (2021) [ 111 ] mHealth apps Perceived benefits Privacy concern Disclosure intention When determining information disclosure, the users’ benefits perception for using mHealth applications is two or three times more influential than their privacy concerns.…”

Section: Table A1mentioning

confidence: 76%

Examining the Intention of Authorization via Apps: Personality Traits and Expanded Privacy Calculus Perspectives

Tang

Zhang

Xiao

2022

Behavioral Sciences

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By integrating the extended privacy calculus theory with the Big Five personality theory, this research proposes and validates a conceptual model in the context of mobile application (App) information authorization. It investigates the implications of each component of privacy costs, privacy advantages, and trust on users’ willingness to authorize their information, and explores how the five personality traits affect App users’ perceived benefits, privacy concern, and trust. Simultaneously, the links between prior negative experience and privacy concern as well as the final authorizing willingness were uncovered. We employed a questionnaire to collect 455 users’ data, and the partial least squares structural equation model (PLS-SEM) was used to test the hypotheses. The findings demonstrate that App users’ perceived benefits and trust have a positive impact on their privacy authorization intention, whereas privacy concerns negatively affect their disclosure willingness. Just as Extraversion and Agreeableness would make someone pay a heightened attention to the benefits, agreeable, neurotic, and conscientious users are more easily stimulated by privacy concern. Respectively, Agreeableness and Neuroticism affect users’ trust positively and negatively. Additionally, prior negative experience will trigger an individual’s privacy concern, which in turn hinders their willingness to authorize his/her information. All of the aforementioned can serve as a guide for App providers as they optimize the features of their products and services, implement the necessary privacy protections to alleviate users’ privacy concern, and boost users’ trust belief. More importantly, these results effectively demonstrate the significance of personal traits in the formation of users’ privacy perceptions.

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“…The information system literature about the technology adoption model primarily predicts behavioral intention, usage intention, or adoption intention as the dependent variable. Most of the studies investigate this variable predictive power through PLS-SEM ( 10 , 34 , 39 ) or CB-SEM ( 35 – 37 , 41 ). One of the primary criteria used to examine the model's predictive capacity is the coefficient of determination ( R 2 ).…”

Section: Discussionmentioning

confidence: 99%

“…The literature review has identified a few studies that employed a two-stage analysis to investigate CTA adoption. Specifically, Duan and Deng ( 37 ) employed CB-SEM with an artificial neural network (ANN) approach to investigate the CTA adoption through the lens of the unified theory of acceptance and use of technology and privacy calculus theory in Australia. In contrast, the study by Nguyen et al ( 39 ) investigated the extended technology adoption model through PLS-SEM and fuzzy set/qualitative comparative analysis (fsQCA).…”

Section: Literature Reviewmentioning

confidence: 99%

“…Research on theory development has highlighted the need for integrating theories and models ( 34 , 36 , 37 , 80 , 89 , 90 ). Based on the TAM, PCT, and the TTF model, this study develops and applies an integrated model to explain behavioral use intention toward the Tawakkalna COVID-19 tracing app, as shown in Figure 2 .…”

Section: Model and Hypotheses Developmentmentioning

confidence: 99%

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Examining the Prediction of COVID-19 Contact-Tracing App Adoption Using an Integrated Model and Hybrid Approach Analysis

Alkhalifah

Bukar

2022

Front. Public Health

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COVID-19 contact-tracing applications (CTAs) offer enormous potential to mitigate the surge of positive coronavirus cases, thus helping stakeholders to monitor high-risk areas. The Kingdom of Saudi Arabia (KSA) is among the countries that have developed a CTA known as the Tawakkalna application, to manage the spread of COVID-19. Thus, this study aimed to examine and predict the factors affecting the adoption of Tawakkalna CTA. An integrated model which comprises the technology acceptance model (TAM), privacy calculus theory (PCT), and task-technology fit (TTF) model was hypothesized. The model is used to understand better behavioral intention toward using the Tawakkalna mobile CTA. This study performed structural equation modeling (SEM) analysis as well as artificial neural network (ANN) analysis to validate the model, using survey data from 309 users of CTAs in the Kingdom of Saudi Arabia. The findings revealed that perceived ease of use and usefulness has positively and significantly impacted the behavioral intention of Tawakkalna mobile CTA. Similarly, task features and mobility positively and significantly influence task-technology fit, and significantly affect the behavioral intention of the CTA. However, the privacy risk, social concerns, and perceived benefits of social interaction are not significant factors. The findings provide adequate knowledge of the relative impact of key predictors of the behavioral intention of the Tawakkalna contact-tracing app.

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Hybrid analysis for understanding contact tracing apps adoption

Cited by 55 publications

References 30 publications

The psychological reassurance effect of mobile tracing apps in Covid-19 Era

The psychological reassurance effect of mobile tracing apps in Covid-19 Era

Examining the Intention of Authorization via Apps: Personality Traits and Expanded Privacy Calculus Perspectives

Examining the Prediction of COVID-19 Contact-Tracing App Adoption Using an Integrated Model and Hybrid Approach Analysis

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