Understanding factors influencing the adoption of mHealth by the elderly: An extension of the UTAUT model
TL;DR: This study confirms the applicability of UTAUT model in the context of mHealth services among the elderly in developing countries like Bangladesh and provides valuable information for mHealth service providers and policy makers in understanding the adoption challenges and the issues.
About: This article is published in International Journal of Medical Informatics.The article was published on 2017-05-01. It has received 556 citations till now. The article focuses on the topics: mHealth & Unified theory of acceptance and use of technology.
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TL;DR: The behavioral intention to use m-learning from the perspective of consumers was explored by applying the extended unified theory of acceptance and use of technology (UTAUT) model with the addition of perceived enjoyment, mobile self-efficacy, satisfaction, trust, and perceived risk moderators.
Abstract: This study developed and empirically tested a model to predict the factors affecting students' behavioral intentions toward using mobile learning (m-learning). This study explored the behavioral intention to use m-learning from the perspective of consumers by applying the extended unified theory of acceptance and use of technology (UTAUT) model with the addition of perceived enjoyment, mobile self-efficacy, satisfaction, trust, and perceived risk moderators. A cross-sectional study was conducted by employing a research model based on multiple technology acceptance theories. Data were derived from an online survey with 1,562 respondents and analyzed using structural equation modeling. Partial least squares (PLS) regression was used for model and hypothesis testing. The results revealed that (1) behavioral intention was significantly and positively influenced by satisfaction, trust, performance expectancy, and effort expectancy; (2) perceived enjoyment, performance expectancy, and effort expectancy had positive associations with behavioral intention; (3) mobile self-efficacy had a significantly positive effect on perceived enjoyment; and (4) perceived risk had a significantly negative moderating effect on the relationship between performance expectancy and behavioral intention. Our findings correspond with the UTAUT model and provide a practical reference for educational institutions and decision-makers involved in designing m-learning for implementation in universities.
382 citations
Cites background or methods or result from "Understanding factors influencing t..."
...According to one study, (Venkatesh et al., 2003; Šumak and Šorgo, 2016; Hoque and Sorwar, 2017; Khalilzadeh et al., 2017; Šumak et al., 2017) PE and EE are direct determinants of BI....
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..., 2017), mobile health (Hoque and Sorwar, 2017), home telehealth services (Cimperman et al....
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...The findings of the study confirmed that PE and EE had significantly positive effects on BI; this was in accordance with the findings of other studies (Venkatesh et al., 2003; Šumak and Šorgo, 2016; Hoque and Sorwar, 2017; Khalilzadeh et al., 2017; Šumak et al., 2017)....
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..., EE, PE, and BI) were adopted from measurement constructs developed in related studies (Venkatesh et al., 2003; Cimperman et al., 2016; Šumak and Šorgo, 2016; Hoque and Sorwar, 2017; Khalilzadeh et al., 2017; Šumak et al., 2017)....
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...Thus, mobile devices are a crucial tool for mobile health, banking, and mobile learning (m-learning) (Alalwan et al., 2017; Briz-Ponce et al., 2017; Hoque and Sorwar, 2017; Nikou and Economides, 2017; Crompton and Burke, 2018)....
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TL;DR: This research provides a novel framework for the exploration of aging barriers and their causes influencing mHealth usability in older adults and identifies a key need for future research on motivational barriers impeding mHealth use of older adults.
231 citations
TL;DR: Effort expectancy is the leading predictor of smart homes for healthcare acceptance among the elderly, together with expert advice, perceived trust, and perceived cost, these four factors represent the key influence of the elderly peoples’ acceptance behavior.
Abstract: Although an Internet-of-Things-based smart home solution can provide an improved and better approach to healthcare management, yet its end user adoption is very low. With elderly people as the main target, these conservative users pose a serious challenge to the successful implementation of smart home healthcare services. The objective of this research was to develop and test a theoretical framework empirically for determining the core factors that can affect the elderly users’ acceptance of smart home services for healthcare. Accordingly, an online survey was conducted with 254 elderly people aged 55 years and above across four Asian countries. Partial least square structural equation modeling was applied to analyze the effect of eight hypothesized predicting constructs. The user perceptions were measured on a conceptual level rather than the actual usage intention toward a specific service. Performance expectancy, effort expectancy, expert advice, and perceived trust have a positive impact on the behavioral intention. The same association is negative for technology anxiety and perceived cost. Facilitating conditions and social influence do not have any effect on the behavioral intention. The model could explain 81.4% of the total variance in the dependent variable i.e., behavioral intention. Effort expectancy is the leading predictor of smart homes for healthcare acceptance among the elderly. Together with expert advice, perceived trust, and perceived cost, these four factors represent the key influence of the elderly peoples’ acceptance behavior. This paper provides the groundwork to explore the process of the actual adoption of smart home services for healthcare by the elderly people with potential future research areas.
198 citations
Cites background from "Understanding factors influencing t..."
...Prior research establishes the relationship between usefulness and intention to use healthcare services [57], [61]....
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TL;DR: Examining the factors affecting the adoption of mHealth services in Bangladesh by using the extended Unified Theory of Acceptance and Use of Technology (UTAUT) model with perceived reliability and price value factors confirmed that performance expectancy, social influence, facilitating conditions and perceived reliability positively influence the behavioral intention to adopt m health services.
178 citations
TL;DR: In this article, the authors investigated the customers' behavioral intention and actual usage of AI-powered chatbots for hospitality and tourism in India by extending the technology adoption model (TAM) with context-specific variables.
Abstract: This study aims to investigate the customers’ behavioral intention and actual usage (AUE) of artificial intelligence (AI)-powered chatbots for hospitality and tourism in India by extending the technology adoption model (TAM) with context-specific variables.,To understand the customers’ behavioral intention and AUE of AI-powered chatbots for tourism, the mixed-method design was used whereby qualitative and quantitative techniques were combined. A total of 36 senior managers and executives from the travel agencies were interviewed and the analysis of interview data was done using NVivo 8.0 software. A total of 1,480 customers were surveyed and the partial least squares structural equation modeling technique was used for data analysis.,As per the results, the predictors of chatbot adoption intention (AIN) are perceived ease of use, perceived usefulness, perceived trust (PTR), perceived intelligence (PNT) and anthropomorphism (ANM). Technological anxiety (TXN) does not influence the chatbot AIN. Stickiness to traditional human travel agents negatively moderates the relation of AIN and AUE of chatbots in tourism and provides deeper insights into manager’s commitment to providing travel planning services using AI-based chatbots.,This research presents unique practical insights to the practitioners, managers and executives in the tourism industry, system designers and developers of AI-based chatbot technologies to understand the antecedents of chatbot adoption by travelers. TXN is a vital concern for the customers; so, designers and developers should ensure that chatbots are easily accessible, have a user-friendly interface, be more human-like and communicate in various native languages with the customers.,This study contributes theoretically by extending the TAM to provide better explanatory power with human–robot interaction context-specific constructs – PTR, PNT, ANM and TXN – to examine the customers’ chatbot AIN. This is the first step in the direction to empirically test and validate a theoretical model for chatbots’ adoption and usage, which is a disruptive technology in the hospitality and tourism sector in an emerging economy such as India.
161 citations
References
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Book•
27 May 1998TL;DR: The book aims to provide the skills necessary to begin to use SEM in research and to interpret and critique the use of method by others.
Abstract: Designed for students and researchers without an extensive quantitative background, this book offers an informative guide to the application, interpretation and pitfalls of structural equation modelling (SEM) in the social sciences. The book covers introductory techniques including path analysis and confirmatory factor analysis, and provides an overview of more advanced methods such as the evaluation of non-linear effects, the analysis of means in convariance structure models, and latent growth models for longitudinal data. Providing examples from various disciplines to illustrate all aspects of SEM, the book offers clear instructions on the preparation and screening of data, common mistakes to avoid and widely used software programs (Amos, EQS and LISREL). The book aims to provide the skills necessary to begin to use SEM in research and to interpret and critique the use of method by others.
42,102 citations
TL;DR: The Unified Theory of Acceptance and Use of Technology (UTAUT) as mentioned in this paper is a unified model that integrates elements across the eight models, and empirically validate the unified model.
Abstract: Information technology (IT) acceptance research has yielded many competing models, each with different sets of acceptance determinants. In this paper, we (1) review user acceptance literature and discuss eight prominent models, (2) empirically compare the eight models and their extensions, (3) formulate a unified model that integrates elements across the eight models, and (4) empirically validate the unified model. The eight models reviewed are the theory of reasoned action, the technology acceptance model, the motivational model, the theory of planned behavior, a model combining the technology acceptance model and the theory of planned behavior, the model of PC utilization, the innovation diffusion theory, and the social cognitive theory. Using data from four organizations over a six-month period with three points of measurement, the eight models explained between 17 percent and 53 percent of the variance in user intentions to use information technology. Next, a unified model, called the Unified Theory of Acceptance and Use of Technology (UTAUT), was formulated, with four core determinants of intention and usage, and up to four moderators of key relationships. UTAUT was then tested using the original data and found to outperform the eight individual models (adjusted R2 of 69 percent). UTAUT was then confirmed with data from two new organizations with similar results (adjusted R2 of 70 percent). UTAUT thus provides a useful tool for managers needing to assess the likelihood of success for new technology introductions and helps them understand the drivers of acceptance in order to proactively design interventions (including training, marketing, etc.) targeted at populations of users that may be less inclined to adopt and use new systems. The paper also makes several recommendations for future research including developing a deeper understanding of the dynamic influences studied here, refining measurement of the core constructs used in UTAUT, and understanding the organizational outcomes associated with new technology use.
27,798 citations
TL;DR: In this paper, the authors developed and tested a theoretical extension of the TAM model that explains perceived usefulness and usage intentions in terms of social influence and cognitive instrumental processes, which was tested using longitudinal data collected regarding four different systems at four organizations (N = 156), two involving voluntary usage and two involving mandatory usage.
Abstract: The present research develops and tests a theoretical extension of the Technology Acceptance Model (TAM) that explains perceived usefulness and usage intentions in terms of social influence and cognitive instrumental processes. The extended model, referred to as TAM2, was tested using longitudinal data collected regarding four different systems at four organizations ( N = 156), two involving voluntary usage and two involving mandatory usage. Model constructs were measured at three points in time at each organization: preimplementation, one month postimplementation, and three months postimplementation. The extended model was strongly supported for all four organizations at all three points of measurement, accounting for 40%--60% of the variance in usefulness perceptions and 34%--52% of the variance in usage intentions. Both social influence processes (subjective norm, voluntariness, and image) and cognitive instrumental processes (job relevance, output quality, result demonstrability, and perceived ease of use) significantly influenced user acceptance. These findings advance theory and contribute to the foundation for future research aimed at improving our understanding of user adoption behavior.
16,513 citations
Book•
01 Jan 2014
TL;DR: The Second Edition of this practical guide to partial least squares structural equation modeling is designed to be easily understood by those with limited statistical and mathematical training who want to pursue research opportunities in new ways.
Abstract: With applications using SmartPLS (www.smartpls.com)—the primary software used in partial least squares structural equation modeling (PLS-SEM)—this practical guide provides concise instructions on how to use this evolving statistical technique to conduct research and obtain solutions. Featuring the latest research, new examples, and expanded discussions throughout, the Second Edition is designed to be easily understood by those with limited statistical and mathematical training who want to pursue research opportunities in new ways.
13,621 citations
Posted Content•
TL;DR: An evaluation of double-blind reviewed journals through important academic publishing databases revealed that more than 30 academic articles in the domain of international marketing (in a broad sense) used PLS path modeling as means of statistical analysis.
Abstract: Purpose: This paper discusses partial least squares path modeling (PLS), a powerful structural equation modeling technique for research on international marketing. While a significant body of research provides guidance for the use of covariance-based structural equation modeling (CBSEM) in international marketing, there are no subject-specific guidelines for the use of PLS so far.Methodology/approach: A literature review of the use of PLS in international marketing reveals the increasing application of this methodology.Findings: This paper reveals the strengths and weaknesses of PLS in the context of research on international marketing, and provides guidance for multi-group analysis.Originality/value of paper: The paper assists researchers in making well-grounded decisions regarding the application of PLS in certain research situations and provides specific implications for an appropriate application of the methodology.
7,536 citations