Modeling and Quantifying User Acceptance of Personalized Business Modes Based on TAM, Trust and Attitude

Zhao, Jie; Fang, Suping; Jin, Peiquan

doi:10.3390/su10020356

Cited by 51 publications

(46 citation statements)

References 41 publications

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“…This result is consistent with the previous findings of technology acceptance studies in which usage intentions have been found to be significantly related to attitudes. In other words, the attitudes had positive effects on usage intentions [56], and the findings were consistent in studies such as Zhu et al [23], Pookulangara and Koesler [24], Dai et al [25], Kumar and Mukherjee [26], Zhao et al [27], and Limpf and Voorveld [28]. Moreover, LBS usage intentions may be examined from theoretical approaches by way of the TAB to provide deeper insight into the attitudes and behaviors of LBS users.…”

Section: Discussionsupporting

confidence: 65%

“…Recently, various TAB studies have been used in a number of field studies, including studies of factors related to the usage intentions of online consumers [23], the willingness of consumers to use mobile commerce [24], consumer usage intentions in the context of social media [25], consumer usage intentions for mobile devices [26], and user usage intentions regarding personalized business modes [27]. According to TAB, the use of technology is determined by people's behavioral intentions, which are determined by their attitudes toward technology.…”

Section: Technology Acceptancementioning

confidence: 99%

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The Impact of Location-Based Service Factors on Usage Intentions for Technology Acceptance: The Moderating Effect of Innovativeness

Jang

Lee

2018

Sustainability

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This study presents features of location-based services (LBS) that influence usage intentions in users and the moderating effects of innovativeness for LBS in sustainable mobile-related industries. As LBS attributes, this study identifies location awareness, reputation, trust, and entertainment. This study model is developed based on technology acceptance behavior (TAB) and is applied to LBS users to identify LBS usage intention factors and TAB perspectives. Research measures are identified and examined on 220 LBS users. The study results are discussed to explore significant factors affecting LBS technology acceptance intentions. The results show that LBS users are more likely to adopt LBS with features of location awareness, reputation, trust, and entertainment. In addition, user attitudes toward LBS are found to play a significant positive role, as are user usage intentions. The moderating effects of personal innovativeness on the relationship between reputation, trust, and entertainment and user attitudes toward LBS are found to be insignificant. The implications for theory and practices are discussed.Location-based services (LBSs), which are offered through mobile devices based on their geographical location, typically provide information, entertainment, tracking, maps and navigation, safety and emergency response options, social networking, commerce, and advertising. Most studies have focused on the privacy concerns of LBS, especially the effects of privacy concerns on user behavior. However, some authors have examined commitment and behavioral intentions to use mobile LBS, user intention to disclose personal information, and intention to use LBS along with usage intent within LBS. Some previous studies explore location-related problems such as location-aware service optimization [2], news apps [3], service center location planning [4], and typhoon hazard location information services [5]. However, little empirical research uses the technology acceptance model (TAM) to examine user attitudes toward LBS and usage intentions [6][7][8][9][10].The purpose of this study is to explore the LBS attributes that affect LBS usage intentions in users by way of the TAM. Based on four LBS attributes (location awareness, reputation, trust, and entertainment), TAM is theoretically justified as influencing users' attitudes. Indeed, the research TAM was developed and empirically examined for this reason. The model uses responses about consumers' intention to use LBS services and products. The specific goals of this study are three-fold. The first goal is to confirm the importance of LBS attributes including location awareness, reputation, trust, and entertainment. Second, to investigate the relationships among these attributes, user attitudes, and usage intentions. Finally, to view LBS as innovative, and therefore, to investigate the moderating role of personal innovativeness in the relationship between these LBS attributes and user attitudes toward LBS. Specifically, this study (1) identifies various LBS attributes (location...

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Section: Discussionsupporting

confidence: 65%

Section: Technology Acceptancementioning

confidence: 99%

The Impact of Location-Based Service Factors on Usage Intentions for Technology Acceptance: The Moderating Effect of Innovativeness

Jang

Lee

2018

Sustainability

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“…Second, because users' decision-making behavior could be impacted by other factors, future work can be focused on other possible factors, such as users' income and education background, review volume or variance, and users' online experience. Finally, it is also worth to study other research models [62] on user acceptance and consider online reviews within the community context [63].…”

Section: Discussionmentioning

confidence: 99%

Shared Short-Term Rentals for Sustainable Tourism in the Social-Network Age: The Impact of Online Reviews on Users’ Purchase Decisions

Zhao

Peng

2019

Sustainability

Self Cite

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With the development of social networks and the Internet-based sharing economy, shared short-term rentals are emerging as a new kind of service that provides a convenient way for people to buy short-term rental services in cities through social-network-enabled platforms. However, like other social-network-based services, shared short-term rental is also likely to be impacted by online reviews. This paper aims to investigate the impact of online reviews on users' purchase decisions toward shared short-term rentals, and further to provide optimization suggestions for the future advance of shared short-term rentals. The contributions of this paper are many-fold. First, we introduce the Stimuli-Organism-Response (SOR) model into the study and propose new variables for the model, including stimulus variables, organism variables, response variable, and moderating variables. Second, we propose eight hypotheses to evaluate the impact of online reviews on users' purchase decisions toward shared short-term rentals. Finally, we collect data through a questionnaire survey and present comprehensive results on many aspects. Based on the data analysis, we find out that the quality of online reviews impacts users' perceived value and perceived risk, which in turn impacts users' purchase decisions toward shared short-term rentals. In addition, the cognitive needs of users can adjust the impact of online reviews on the perceived risk of users but have no explicit adjusting effect for users' perceived value. Further, we present some research implications as well as suggestions for rental platforms to advance shared short-term rentals in the Internet age.

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“…According to a recent survey [1], over 90% of Europeans are using social-network sites. Owing to the advantages of social networks, many companies have integrated social networks into innovation of business modes [2]. For instance, Coca-Cola developed "Lyrics Bottle" [3], which is a social-network application.…”

Section: Introductionmentioning

confidence: 99%

“…(1) What factors influence user willingness toward knowledge sharing in social networks? (2) How do these factors impact user willingness toward knowledge sharing in social networks? Knowledge sharing is helpful for organizations and enterprises to improve their knowledge management and learning innovation.…”

Section: Introductionmentioning

confidence: 99%

User Willingness toward Knowledge Sharing in Social Networks

et al. 2018

Self Cite

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Social networks introduce new potential for people to share knowledge with others. However, it is not clear what factors influence user willingness toward knowledge sharing in social networks. Aiming to answer these questions, in this paper we analyze the major factors influencing user willingness toward knowledge sharing in social networks and propose a new research model that is inspired by the technology acceptance model (TAM). In particular, we introduce a new independent variable called perceived value which is described by four aspects: social value, entertainment value, emotion value, and information value. In addition, we introduce a new mediating variable, trust, to reflect the intermediating relationship between perceived value and knowledge-sharing willingness. We conduct an empirical analysis on questionnaire data and present comprehensive results on reliability and validity, factor analysis, correlation analysis, and mediating effects analysis. The results show that perceived value has a significant impact on knowledge-sharing willingness, and trust plays a partial intermediate role between perceived value and knowledge-sharing willingness. Further, we present some research implications for knowledge sharing and learning innovation in social networks, as well as some suggestions for organizations to advance knowledge sharing and learning innovation in the social-network age.

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Modeling and Quantifying User Acceptance of Personalized Business Modes Based on TAM, Trust and Attitude

Cited by 51 publications

References 41 publications

The Impact of Location-Based Service Factors on Usage Intentions for Technology Acceptance: The Moderating Effect of Innovativeness

The Impact of Location-Based Service Factors on Usage Intentions for Technology Acceptance: The Moderating Effect of Innovativeness

Shared Short-Term Rentals for Sustainable Tourism in the Social-Network Age: The Impact of Online Reviews on Users’ Purchase Decisions

User Willingness toward Knowledge Sharing in Social Networks

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