Determinants of accepting wireless mobile data services in China

Lu, June; Liu, Chang; Yu, Chun‐Sheng; Wang, Kanliang

doi:10.1016/j.im.2007.11.002

Cited by 304 publications

(201 citation statements)

References 22 publications

(19 reference statements)

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“…Previous works have shown that, as theorized in the original TAM, perceived usefulness has both a direct effect and an indirect effect via ease of use on intention to use [21,23,27,53]. In addition, the Van der Heijden's model [24] provides some evidence that it has an indirect impact on intention to use through perceived ease of use as well as perceived enjoyment.…”

Section: Research Model and Hypothesesmentioning

confidence: 98%

The moderating role of prior experience in technological acceptance models for ubiquitous computing services in urban environments

Torres

Díaz‐Fernández

Toral

et al. 2015

Technological Forecasting and Social Change

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Ubiquitous computing services constitute a new information technology that can be used in thousands of potential applications and environments. Ubiquitous computing is also changing the classic paradigm of information technology as it is forcing social and cultural changes. Determining factors affecting the use of ubiquitous services is essential to correctly define the characteristics of new value added services. However, this study investigates not only these factors, but also the moderating effect of previous experience. Due to the technological nature of ubiquitous services, previous experience alters the way in which potential users face these services. Findings suggest that previous experience changes the way in which antecedent relates to basic TAM constructs. The derived research models and empirical results also provide valuable indicators for future research and managerial guidelines for the successful adoption of ubiquitous computing services.

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Section: Research Model and Hypothesesmentioning

confidence: 98%

The moderating role of prior experience in technological acceptance models for ubiquitous computing services in urban environments

Torres

Díaz‐Fernández

Toral

et al. 2015

Technological Forecasting and Social Change

View full text Add to dashboard Cite

show abstract

“…For instance, children might support and persuade their parents to adopt mobile health care due to their poor health status. Social regulation influences consumers' behavior intention [69][70][71][72]. In the mobile health care service field, social regulation is one of the most important influence factors in consumer adoption [73].…”

Section: Analysis Of the Characteristics And Adoption Of Mobile Healtmentioning

confidence: 99%

Key Influence Factors of Consumers� Intentions Towards Mobile Health Care Promotion: An Empirical Study Based on the DDANPMV Model

Liu¹,

Yang²,

Liu³

et al. 2017

Preprint

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IntroductionMobile health care is an important aspect of electronic medicine that involves using mobile devices (e.g., mobile phones, tablet computers, and personal digital assistants) to provide medical services and health information to patients [1]. Health care faces numerous problems, including high medical costs, restricted coverage, complex medical procedures, and uneven distribution of resources [2]. Mobile health care can help to reduce medical costs and waiting times and improve the efficiency of medical resources use [3]. Mobile health care involves the following categories [4]: (1) Mobile phone applications such as Chun Yu Yi Sheng, which acts as an information exchange platform linking doctors and patients, and comprehensive mobile health care platforms that hospital service providers can apply for appointment registrations, payments, and medical alerts. (2) The collection of users' medical data through wearable devices or mobile intelligent terminals for health monitoring. For example, Kangkang launched a portable intelligent sphygmomanometer that can dynamically monitor blood pressure over a 24-hour period and automatically send data to a corresponding server. Users can view their 24-hour blood pressure analysis report through WeChat. (3) Diagnosis systems that connect with the Internet of Things (IoT). For example, an integrated diagnosis system developed by German researchers can transmit medical data to smart phones through Bluetooth technology. Smartphones applications can then process these data for reference and diagnosis.With the development of mobile networks, many countries have entered the 4G era and benefit from continuously improving mobile communication networks and innovation in software and hardware technology. Abstract: Identifying the key influence factors of mobile health care adoption is a key issue. We established an evaluation index system for consumer adoption and verified the effectiveness of our model by using a DDANPMV model. This model comprises three parts: (1) the decision making trial and evaluation laboratory (DEMATEL) technique, which is used to establish an influence network relationship map at both the "dimensions" and "criteria" levels; (2) a DEMATEL-based analytic network process (ANP; DANP), which determines the interrelationships and influential weights among the criteria; and (3) a modified VlseKriterijumska Optimizacija I Kompromisno Resenje (VIKOR) method, which applies the influence weights obtained through DANP to performance gaps regarding consumer perception. VIKOR thereby evaluates and improves performance gaps with the aims of satisfying consumer needs, achieving continuous improvement, and enabling sustainable product development. The main innovation of this method is the construction of the DDANPMV model, which integrates the DEMATEL, DANP, and modified VIKOR approaches to examine consumers' adoption of mobile health care. This method was developed to not only help decision-makers evaluate alternative mobile health care and determine the best option b...

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“…• Performance expectancy: this construct consisted four items; two of them were adopted from Li and Yeh (2009), while the other two items were adopted from Lu, Liu, Yu, and Wang (2008).…”

Section: Measures Of the Studymentioning

confidence: 99%

Mediating Effects of Behavioral Intention Between 3g Predictors and Service Satisfaction

Dhaha¹,

Ali²

2014

JKMJC

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IsmaIl sheIkh Yusuf ahmed dhaha InternatIonal IslamIc unIversItY malaYsIa alI YassIn sheIkh alI sudan unIversItY of scIence and technologY, khartoum, sudan Abstract This paper looks at the factors that affect the adoption and satisfaction with third generation (3G) mobile phones among students at a private university in Somalia from the perspective of the Unified Theory of Acceptance and Use of Technology (UTAUT. Specifically, the objectives of the study are to 1) examine the effect of performance expectancy on students' intention to adopt 3G; 2) explore the effect of effort expectancy on students' intension; 3) look at the effect of social influence on students' intention; 4) examine the effect of perceived expense on students' intention; 5) test the effect of intention on students' satisfaction with the service; and finally 6) test the mediating effect of intention between 3G predictors and satisfaction with the service. The study uses proportionate stratified random sampling procedure, where the faculty and gender were the main strata. The data were collected in June 2013 and a total of 395 students responded to the study. The data was analyzed using SPSS version 17.0 to answer research objectives and test its hypotheses. Using multipleStep-Wise regression, the results suggested that performance expectancy (β=.158, t=2.850, p=.005), effort expectancy (β=.106, t=2.094, p=.037), social influence (β=.358, t=6.888, p=.000), and perceived expense (β=.165, t=3.872, p=.000) had significant and positive effects on students' intention to adopt 3G mobile technology. However, social influence (β=.358) was the best (Special Issue) 2014: 107-128 108 predictor for the students' intention followed by perceived expense (β=.165). Furthermore, behavioral intention significantly mediated the relationships of predictors with satisfaction. Implications and future research scope are discussed.

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Determinants of accepting wireless mobile data services in China

Cited by 304 publications

References 22 publications

The moderating role of prior experience in technological acceptance models for ubiquitous computing services in urban environments

The moderating role of prior experience in technological acceptance models for ubiquitous computing services in urban environments

Key Influence Factors of Consumers� Intentions Towards Mobile Health Care Promotion: An Empirical Study Based on the DDANPMV Model

Mediating Effects of Behavioral Intention Between 3g Predictors and Service Satisfaction

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