Understanding online group buying intention: the roles of sense of virtual community and technology acceptance factors

Tsai, Ming‐Tien; Cheng, Nai‐Chang; Chen, Kun-Shiang

doi:10.1080/14783363.2011.614870

Cited by 103 publications

(93 citation statements)

References 38 publications

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“…The value of NFI was 0.99, CFI was 0.99, IFI was 0.99, GFI was 0.94, AGFI was 0.91, and RMSEA was 0.073. The overall results suggested that the research model provided an adequate fit to the data (Hair et al, 1998;Tsai, Cheng and Chen, 2011). H1-H4 predicted that injunctive norms, descriptive norms, social identity, and group norms exert a positive influence on continued usage intention for MSNAs.…”

Section: Model Fit Assessment and Resultsmentioning

confidence: 95%

Examining social influence factors affecting consumer continuous usage intention for mobile social networking applications

Wang

Chou

2016

IJMC

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Due to the rapid increase in the use of mobile devices, mobile socialnetworking applications (MSNAs) have proliferated during recent years. MSNAs can provide social groups with a means to communicate among group members. Although studies have shown that social influence is relevant to individual and group collective behaviour, few studies have investigated the predictive relationships between multiple integrated social influence factors and the behavioural intention for the use of MSNAs. Therefore, we examined the effects of social influence factors (injunctive norms, descriptive norms, social identity, and group norms) on the continued intentions to use MSNAs. Data collected though the website of an online survey company yielded 830 usable questionnaires. We used structural equation modelling (SEM) to test the hypothesised relationships. The results indicate that injunctive norms, descriptive norms, and social identity were positively related to continued usage intention, whereas group norms were unrelated to continued usage intention. Understanding consumer decisions regarding the repeated use of an MSNA is necessary for mobile application (M-app) developers to design programs that ensure user retention.

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Section: Model Fit Assessment and Resultsmentioning

confidence: 95%

Examining social influence factors affecting consumer continuous usage intention for mobile social networking applications

Wang

Chou

2016

IJMC

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“…Both PEU and PU have a significant effect on the hospitality students' intention to use M-Learning. The effect that PU has on IU has been addressed in prior academic research [32], [33], but how PEU affects IU remains controversial in academia as, whereas several scholars [23] posit that PEU has a significant effect on IU, others [11] disagree. The results of this study showed that for hospitality students, the PEU of an M-Learning course would have a significant effect on their intention to use M-Learning.…”

Section: Discussionmentioning

confidence: 99%

“…Therefore, PEU of M-Learning should be the primary concern when designing the M-Learning. Hospitality students' intention to use M-Learning has a negative effect on their self-learning effectiveness; hence, practitioners are encouraged to teach learners various strategies to help them familiarize themselves with this innovative way of learning in order to optimize their self-learning effectiveness [32].…”

Section: Discussionmentioning

confidence: 99%

Examining Effectiveness of m-Learning in Hospitality Education with Revised Technology Acceptance Model

Hsu¹,

Tourism²,

Chen³

2018

IJIET

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Abstract-This study explored the effectiveness of using mobile devices in the learning of hospitality subjects. Four hundred and thirty-seven (437) high school students in a hospitality program in Taiwan participated in this survey and the revised technology acceptance model (TAM) was adopted as the major research instrument. Seven research hypotheses were posited. The results of statistical analysis indicated that participants regarded perceived ease of use (PEU) as being more important than perceived usefulness (PU) when M-Learning (a combination of mobile device and e-learning) is designed to be integrated in teaching and learning hospitality subjects. Five of the seven research hypotheses were supported by the structural equation model (SEM). Specifically, this study found that the genre of courses (academic course and practical course) did not significantly lead to either PEU or PU but it resulted significantly in participants' having different behavioral intention to use (IU) M-Learning. Moreover, PEU as well as PU were significantly related to IU. Counterintuitively, IU has a significantly negative effect on the effectiveness of self-learning.

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“…OGB is a new business model that has not been fully investigated. For instance, prior research focused mainly on issues regarding OGB shoppers' behavioural intention (e.g., Cheng and Huang 2013, Shiau and Luo 2012, Tsai et al 2011) and the functionality and usage of group buying systems (e.g., Tan et al 2007, Wang and Chou 2014, Zhang et al 2014 as well as the influences on consumers utilitarian and hedonic benefits (e.g., Chiu et al 2014, Shiau and Wu 2013.…”

Section: Introductionmentioning

confidence: 99%

Consumer benefit creation in online group buying: The social capital and platform synergy effect and the mediating role of participation

Chen

Peng

et al. 2015

Electronic Commerce Research and Applications

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Understanding online group buying intention: the roles of sense of virtual community and technology acceptance factors

Cited by 103 publications

References 38 publications

Examining social influence factors affecting consumer continuous usage intention for mobile social networking applications

Examining social influence factors affecting consumer continuous usage intention for mobile social networking applications

Examining Effectiveness of m-Learning in Hospitality Education with Revised Technology Acceptance Model

Consumer benefit creation in online group buying: The social capital and platform synergy effect and the mediating role of participation

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