Exploring the influential factors of continuance intention to use mobile Apps: Extending the expectation confirmation model

Tam, Carlos; Santos, Diogo Soares dos; Oliveira, Tiago

doi:10.1007/s10796-018-9864-5

Cited by 371 publications

(350 citation statements)

References 76 publications

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“…The empirical results showed that the satisfaction of previous learning experience, the confirmation of previous learning experience and perceived usefulness had significant effects on the willingness to continue using. Tam ， Santos and Oliveira (2018) [19] based on the expectation-confirmation model (ECM) and extended unified theory of acceptance and use of technology (UTAUT2), discussed the factors of the willingness to continue using mobile applications, and found that the most important factors of the continuance intentions using mobile applications were satisfaction and confirmation expectation.…”

Section: B Expectation-confirmation Model In the Context Of E-readingmentioning

confidence: 99%

Exploring the Influencing Factors of Undergraduates' Continuance Intentions in e-Reading APPs (EIFUCIEA)

Lai¹,

Zhao²

2019

IJIET

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Electronic reading (e-reading) becomes a common way of reading for undergraduates. Many e-reading applications (APPs) are designed to satisfy the readers' reading needs. But there is no such a study focus on using expectancy confirmation theory to examine undergraduates' continuance intentions (UCI) of reading APPs. Then to address this gap, this study was to investigate the influencing factors of UCI of reading APPs in a Chinese university. Based upon the EECM-IT model and DeLong &McLean (D&M) information system success model, the variables of Subjective Norm (SN) and Perceived Risk (PR) were introduced to the UCI model of e-reading and twelve hypotheses were proposed. The study adopted the confirmatory factor analysis method to examine the structural model. From data analysis, the results showed that undergraduates' expected confirmation of e-reading APPs was significantly affected by subjective norms, and significantly affected perceived ease of use, perceived risk, reading usefulness and user's satisfaction. However, satisfaction was not significantly affected by perceived risk and perceived ease of use. Subjective norms did not significantly affect continuance intentions. Additionally, there was no gender or grade difference among undergraduates' continuance intentions, which was only significantly related to their majors.

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Section: B Expectation-confirmation Model In the Context Of E-readingmentioning

confidence: 99%

Exploring the Influencing Factors of Undergraduates' Continuance Intentions in e-Reading APPs (EIFUCIEA)

Lai¹,

Zhao²

2019

IJIET

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“…Perceived ease of use can induce users to engage more with the given technology [2,3], while complexity can have a negative impact on users' intention to adopt or reuse it [80]. For mobile apps usage, EE remains one of the crucial factors and significantly effects the behavioral intention of a user [81,82]. Similarly, operational comfort and complications involved can meaningfully influence users' intention to use mobile news apps.…”

Section: Effort Expectancy (Ee)mentioning

confidence: 99%

“…Habit was observed to have an effect on consumers' intention to use mobile payments [70], mobile apps [81], and the actual use of internet banking services [96]. Moreover, Barnes [97] stated that continuance intention can be determined by habit, while Tam and Santos [82] showed that for continuous intention to use mobile apps, habit is an influential predictor.…”

Section: Habit (Ha)mentioning

confidence: 99%

Role of Personalization in Continuous Use Intention of Mobile News Apps in India: Extending the UTAUT2 Model

Cheng

Sharma

et al. 2020

Information

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The aim of this study was to empirically examine the extended unified theory of acceptance and use of technology 2 (UTAUT2) model by adding “personalization” as one of the antecedents, as well as a moderator to determine the key factors for the continuous use intention of mobile news applications (apps). For this study, an online and manual sample survey of 309 respondents, who had used the news app earlier, was collected and analyzed, using quantitative methods such as explanatory and confirmatory factor analysis, structural equation modeling, and Hayes process for finding moderating effects among variables. The findings of the direct effect demonstrated that performance expectancy (PE) has the most influential effect on continuous use intention, followed by habit (HT), hedonic motivation (HM), and facilitating conditions (FC). Furthermore, the outcome of tests for the moderating effect of personalization between UTAUT2 constructs and continuous use intention (CUI) showed that personalization has a significant moderating effect on performance expectancy and habit. Therefore, this research establishes the key role of PE, HT, HM, and FC as main factors that trigger the users’ continuous use intention of news apps and provides an integrated framework to assess the moderating effect of personalization on technology acceptance. The findings of the research expand the existing literature on news applications and provide foundation for future research studies in the area of mobile news apps.

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“…Positioning and timeliness refer to the value that LBA user perceive from having access to information and services in the right time and at the right place [73]. Users benefit expectation refers to their anticipated gained through using an information system [39,65]. When users expect more benefits from using LBAs, they are more likely to perceive the LBA useful.…”

Section: Hypotheses Developmentmentioning

confidence: 99%

Continued Usage and Location Disclosure of Location-Based Applications: A Necessity for Location Intelligence

Koohikamali¹,

Mousavizadeh²,

Peak³

2019

Proceedings of the Annual Hawaii International Conference on System Sciences

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Location-based applications (LBA) have been widely accepted and used for different purposes ranging from navigation to dating or gaming. Most LBAs ask users to provide access to location data for more efficient and personalized location-based services. Location intelligence as an emerging area of business intelligence relies heavily on disclosing location information by users. This research builds a continuance usage and location disclosure model from the expectation-confirmation perspective. The effect of benefit expectations on usefulness and satisfaction is hypothesized. In addition, the positive effect of usefulness on satisfaction and continuance intention is postulated. After collecting survey data from main LBA users, the results of the analysis support the proposed model. Findings contribute to the current literature in business intelligence by focusing on location disclosure behavior in the context of LBAs and the necessity of this type of information for location intelligence.

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Exploring the influential factors of continuance intention to use mobile Apps: Extending the expectation confirmation model

Cited by 371 publications

References 76 publications

Exploring the Influencing Factors of Undergraduates' Continuance Intentions in e-Reading APPs (EIFUCIEA)

Exploring the Influencing Factors of Undergraduates' Continuance Intentions in e-Reading APPs (EIFUCIEA)

Role of Personalization in Continuous Use Intention of Mobile News Apps in India: Extending the UTAUT2 Model

Continued Usage and Location Disclosure of Location-Based Applications: A Necessity for Location Intelligence

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