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Social Presence, Trust, and Social Commerce Purchase Intention: an Empirical Research.

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TLDR
The social presence factors are found to have positive impacts on trust in sellers, and a multi-dimensional model of social presence is proposed, which delineates a full picture of online buyer behaviors in social commerce.
About
This article is published in Pacific Asia Conference on Information Systems.The article was published on 2014-01-01 and is currently open access. It has received 540 citations till now. The article focuses on the topics: Empirical research.

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Living up to the chatbot hype: The influence of anthropomorphic design cues and communicative agency framing on conversational agent and company perceptions

TL;DR: This study investigates the relevance of anthropomorphism and social presence to important company-related outcomes, such as attitudes, satisfaction and the emotional connection that consumers feel with the company after interacting with the chatbot.
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The role of live streaming in building consumer trust and engagement with social commerce sellers

TL;DR: In this article, a comprehensive framework was proposed to examine the relationship among customers' perceived value of live streaming, customer trust, and engagement, while utilitarian and hedonic values are shown to affect customer engagement indirectly through customer trust in products and trust in sellers sequentially.
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How live streaming influences purchase intentions in social commerce: An IT affordance perspective

TL;DR: This study examines how live streaming influences social commerce customers’ purchase intentions in China by building a theoretical model from the perspective of IT affordance and empirically measure the model by surveying customers who have shopped via live streaming shopping platforms.
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Modelling and testing consumer trust dimensions in e-commerce

TL;DR: A path model is empirically test such that Internet vendors would have adequate solutions to increase trust and suggests that consumers with high overall trust demonstrate a higher intention to purchase online.
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Investigating the drivers for social commerce in social media platforms: Importance of trust, social support and the platform perceived usage

TL;DR: In this paper, the authors explored the perceived characteristics of the social commerce vendor and investigated their influence on users' trust in social media platforms and found that reputation and price advantage have the strongest influence on trust, although those effects are weakened by habits.
References
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The theory of planned behavior

TL;DR: Ajzen, 1985, 1987, this article reviewed the theory of planned behavior and some unresolved issues and concluded that the theory is well supported by empirical evidence and that intention to perform behaviors of different kinds can be predicted with high accuracy from attitudes toward the behavior, subjective norms, and perceived behavioral control; and these intentions, together with perceptions of behavioral control, account for considerable variance in actual behavior.
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Evaluating Structural Equation Models with Unobservable Variables and Measurement Error

TL;DR: In this paper, the statistical tests used in the analysis of structural equation models with unobservable variables and measurement error are examined, and a drawback of the commonly applied chi square test, in additit...
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Common method biases in behavioral research: a critical review of the literature and recommended remedies.

TL;DR: The extent to which method biases influence behavioral research results is examined, potential sources of method biases are identified, the cognitive processes through which method bias influence responses to measures are discussed, the many different procedural and statistical techniques that can be used to control method biases is evaluated, and recommendations for how to select appropriate procedural and Statistical remedies are provided.
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Multivariate data analysis

TL;DR: This chapter discusses Structural Equation Modeling: An Introduction, and SEM: Confirmatory Factor Analysis, and Testing A Structural Model, which shows how the model can be modified for different data types.
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