Perceived usefulness predicts second language learners’ continuance intention toward language learning applications: a serial multiple mediation model of integrative motivation and flow

Wang, Xuebin; Lu, Aitao; Lin, Tao; Liu, Siyi; Song, Tianhua; Huang, Xin; Jiang, Lilan

doi:10.1007/s10639-021-10822-7

Cited by 19 publications

(13 citation statements)

References 60 publications

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“…The survey of smart tourism proves the negative effect of sensing the wind direction of tourism technology on tourism behavior intention, among which the ease of use of intelligent tourism technology may reduce the perception of risks, thereby forming tourism intention (Huang & Lau, 2020). Wang et al (2022) surveyed Chinese and American college students and clarified that the perceived usefulness of mobile payment might mediate the path of perceived risk and consumption intention.…”

Section: Literature Review and Hypothesesmentioning

confidence: 99%

“…Behavioral intention has long been an essential indicator of predictive behavior, and PRT suggests that risk perception may negatively affect behavioral intention and specific behavior (Kamalul Ariffin et al, 2018). As the primary payment method of Chinese and American college students, their perception of payment risk negatively affects their willingness to make mobile payments in an unfamiliar environment, and their payment behavior will be affected (Wang et al, 2022). In sustainable consumption research, the willingness to consume sustainably also often plays a mediating role in influencing the significance of external variables on sustainable consumption behavior (Jiang et al, 2022).…”

Section: Literature Review and Hypothesesmentioning

confidence: 99%

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Toward the digital economy: Mobile payment affecting sustainable consumption behavior

Yuan

Jiang

Cruz

2023

Innovative Marketing

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Mobile payment has a pronounced impact on the consumption mode of various industries and provides new clues for sustainable consumption. This study aims to explore the role of perceived risk and perceived technology on sustainable consumption intention and behavior. Moreover, it proposes the structural equation model of mobile payment for sustainable consumption behavior. 574 participants from Chinese higher education institutions filled in the questionnaire. The bootstrapping method was used to solve the problem of mediating factors. Amos 26.0 helped to construct structural equation models. The study determined the negative effect of the perceived mobile payment risk on the perceived mobile payment usefulness, perceived mobile payment ease of use, and sustainable consumption intention. Moreover, the three variables have a particular buffer in the relationship between perceived mobile payment risk and sustainable consumption behavior. Furthermore, perceived mobile payment usefulness positively impacts sustainable consumption intention, and they have a chain-mediated effect on the relationship between perceived mobile payment risk and sustainable consumption behavior. The same effect also occurs in the relationship between perceived mobile payment ease of use and sustainable consumption intention.

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Section: Literature Review and Hypothesesmentioning

confidence: 99%

Section: Literature Review and Hypothesesmentioning

confidence: 99%

Toward the digital economy: Mobile payment affecting sustainable consumption behavior

Yuan

Jiang

Cruz

2023

Innovative Marketing

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“…Consequently, a recent study by Ashfaq et al (2020) found PU to be a significant contributor towards the continuance use of chatbots. However, recent studies have also found a significant influence of PU on CIs to use technology (Nguyen et al, 2021;Khlaif et al, 2022;Wang et al, 2022). Furthermore, extant studies have also studied the significant influence of PU on satisfaction in the context of information technology (Thong et al, 2006) and smart fitness wearables (Gupta et al, 2020;Nong et al, 2022;Akdim et al, 2022).…”

Section: Perceived Usefulnessmentioning

confidence: 99%

Tourists’ post-adoption continuance intentions of chatbots: integrating task–technology fit model and expectation–confirmation theory

Dhiman

Jamwal

2022

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Purpose Despite the proliferation of service chatbots in the tourism industry, the question on its continuance intentions among customers has largely remain unanswered. Building on an integrated framework using the task–technology fit theory (TTF) and the expectation–confirmation model (ECM), the present study aims to settle this debate by investigating the factors triggering customers to continue to use chatbots in a travel planning context. Design/methodology/approach The research followed a quantitative approach in which a survey of 322 chatbot users was undertaken. The model was empirically validated using the structural equation modelling approach using AMOS. Findings The results reveal that users’ expectations are confirmed when they believe that the technological characteristics of chatbots satisfy their task-related characteristics. Simply, the results reveal a significant and direct effect of TTF on customers’ confirmation and perceived usefulness towards chatbots. Moreover, perceived usefulness and confirmation were found to positively impact customers’ satisfaction towards chatbots, in which the former exerts a relatively stronger impact. Not surprisingly, customers’ satisfaction with the artificial intelligence(AI)-based chatbots emerged as a predominant predictor of their continuance use. Practical implications The findings have various practical ramifications for developers who must train chatbot algorithms on massive data to increase their accuracy and to answer more exhaustive inquiries, thereby generating a task–technology fit. It is recommended that service providers give consumers hassle-free service and precise answers to their inquiries to guarantee their satisfaction. Originality/value The present work attempted to empirically construct and evaluate the combination of the TTF model and the ECM, which is unique in the AI-based chatbots available in a tourism context. This research presents an alternate method for understanding the continuance intentions concerning AI-based service chatbots.

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“…It indicates the research model in this study gained good explanatory power. Perceived usefulness (β = 0.593, p < 0.001) significantly impacted continuance intention [54][55][56]. Satisfaction (β = 0.397,…”

Section: Hypothesis Testingmentioning

confidence: 99%

Satisfaction and continuance intention of blended learning from perspective of junior high school students in the directly-entering-socialism ethnic communities of China

Phongsatha

2022

PLoS ONE

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Background Blended learning in DESEC only started after the introduction of the internet in recent 5 years. However, there is still no research paying attention to this region, because the area is remote and research subjects are not easily accessible. This article has potential application value in helping the government and educational institutions to make decisions on blended learning strategies supporting poverty alleviation through education in poor and remote areas and ethnic region. The study will be the first to examine satisfaction and continuance intention of blended learning in the DESEC. Objective To identify junior high students’ perception of satisfaction and continuance intention for blended learning in DESEC. To identify the strongest factors affecting junior high students’ satisfaction and continuance intention of blended learning in DESEC. Methods A subsample of 635 junior high students participated online survey with consent of their parents verbally in computer room in schools under teacher’s instruction. Data was coded and analyzed to generate descriptive statistics and inferential statistics. Structural equation model was used to evaluate the model of satisfaction and continuance intention of blended learning. Results The level for evaluating students’ agreement on each of item were interpreted “agree” (3.76–3.89). The model explained variances (R2) of Continuance Intention, Satisfaction and Perceived usefulness were 0.665,0.766,0.718 respectively. Information quality, self-efficacy and confirmation directly and indirectly contribute to junior high students’ satisfaction with blended learning, which further confirmed their continuance intention of blended learning. Conclusion Information quality was the strongest factor affecting the junior high students’ continuance intention of using blended learning, while confirmation was the strongest factor affecting the junior high students’ satisfaction of using blended learning in DESEC. Junior high students do not have a strong and distinct perception on satisfaction and continuance intention for blended learning in DESEC.

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Perceived usefulness predicts second language learners’ continuance intention toward language learning applications: a serial multiple mediation model of integrative motivation and flow

Cited by 19 publications

References 60 publications

Toward the digital economy: Mobile payment affecting sustainable consumption behavior

Toward the digital economy: Mobile payment affecting sustainable consumption behavior

Tourists’ post-adoption continuance intentions of chatbots: integrating task–technology fit model and expectation–confirmation theory

Satisfaction and continuance intention of blended learning from perspective of junior high school students in the directly-entering-socialism ethnic communities of China

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