What creates trust and who gets loyalty in social commerce?

Yeon, Jewoo; Park, Inyoung; Lee, Daeho

doi:10.1016/j.jretconser.2019.05.009

Cited by 70 publications

(53 citation statements)

References 58 publications

Supporting

Mentioning

Contrasting

Unclassified

Order By: Relevance

“…This finding is also consistent with prior research in the context of s-commerce (e.g. Akman & Mishra, 2017;Chen et al, 2021;Lin & Wu, 2015;Sheikh et al, 2019;Shin, 2013;Yeon et al, 2019). Al-Adwan (2019) argues that when a consumer develops a positive purchase intention from using a particular s-commerce platform, it leads to a higher probability that he/she will perform an actual purchase.…”

Section: Resultssupporting

confidence: 89%

“…The effect of behavioral intention on technology use is well established within the literature (Chopdar et al, 2018;Dwivedi et al, 2019;Venkatesh et al, 2012). A limited number of studies have investigated the impact of behavioral intention on use behavior in the context of scommerce (Akman & Mishra, 2017;Al-Adwan, 2019;Chen et al, 2021;Hashim et al, 2015;Lin & Wu, 2015;Sheikh et al, 2019;Shin, 2013;Yeon et al, 2019). For example, Sheikh et al (2019) found that s-commerce intentions have a significant effect on use behavior by using data collected from 343 SNS users from Pakistan.…”

Section: Behavioral Intentionmentioning

confidence: 99%

See 1 more Smart Citation

A Meta-Analytic Structural Equation Model for Understanding Social Commerce Adoption

et al. 2021

View full text Add to dashboard Cite

Social commerce (s-commerce) has gained prominence with advances in social media and social networking technologies over the last decade. Prior research has employed diverse theoretical perspectives to understand and explain consumer behavior within s-commerce but has also produced inconsistent results. This study integrates different theoretical perspectives including trust, social support, and social presence. The research portrays an integrated research model involving factors that impact behavioral intention and use behavior of s-commerce consumers whilst synthesizing prior empirical findings. A meta-analytic structural equation modeling (MASEM) method was used to synthesize 189 findings reported in 68 s-commerce studies and to analyze the structural model. Our findings show that trust and informational support have positive effects on behavioral intention while trust and emotional support have positive effects on use behavior. Furthermore, our findings highlight that behavioral intention influences use behavior and mediates the effect of trust and informational support on use behavior. The implications for research and practice are discussed in detail.

show abstract

Section: Resultssupporting

confidence: 89%

Section: Behavioral Intentionmentioning

confidence: 99%

A Meta-Analytic Structural Equation Model for Understanding Social Commerce Adoption

et al. 2021

View full text Add to dashboard Cite

show abstract

“…In addition, when there exists high level of RSC between two individuals, they are more willing to engage in resources exchange [12,78] and then enhance consumers' intention to buy [73]. Thirdly, RSC is positively linked to consumers' attitudes [79] and consumers' satisfaction [80], which can in turn positively influence consumers' intention to buy.…”

Section: Rsc: Trust In Peers and Reciprocitymentioning

confidence: 99%

Understanding Consumers’ Purchase Intentions in Social Commerce through Social Capital: Evidence from SEM and fsQCA

Yang

2021

JTAER

View full text Add to dashboard Cite

Social commerce has become a fiercely competitive environment. Understanding consumers’ purchase intentions can help social commerce platforms retain and attract more consumers. Social capital is one of the primary resources that plays a critical role in facilitating consumers’ purchase intentions in social commerce. Here, complex relationships between different dimensions of social capital are further clarified and its impact on consumers’ purchase intentions are discussed. Based on a survey of 302 social commerce users, this study utilizes an SEM and fsQCA approach to validate the effect of social capital on consumers’ purchase intentions. The SEM results reveal that the effect of structural social capital on consumers’ purchase intentions is fully mediated by relational and cognitive social capital. The fsQCA results confirm the significance of consumers’ social capital as determinants and provide the configurations that can lead to high purchase intentions. Though previous studies have discussed the factors influencing consumers’ purchase intentions, this study takes the first step toward enhancing the understanding of the configurations that link dimensions of social capital to consumers’ purchase intentions in s-commerce using fsQCA approach.

show abstract

“…Indeed, if Twitter users trust that platform, they will continue to use it and, through a process of trust transfer, they will trust the brands they follow and visit their websites to purchase products. In the context of social e‐commerce, defined as ‘forms of Internet‐based social media that allow people to participate actively in the marketing and selling of products in online marketplaces and communities’ (Stephen & Toubia, 2010, p. 215), trust has a ‘vital influence on the transaction process’ (Yeon et al, 2019). Thus, in this study, we consider trust as a construct combining two sub‐constructs: trust in the fashion brand and trust in the social media platform used.…”

Section: Theoretical Frameworkmentioning

confidence: 99%

How trust leads to online purchase intention founded in perceived usefulness and peer communication

Harrigan

Feddema

Wang

et al. 2021

J of Consumer Behaviour

View full text Add to dashboard Cite

This study seeks to understand the specific factors on social media that help drive the intention to purchase fashion‐related products, focusing on the central role of trust. The unique contribution of this research lies in its exploration of the interplay between perceived usefulness of the fashion brand's social media and peer communication on the fashion brand's social media in driving trust in the fashion brand's social media and, ultimately, purchase intention. Theoretically, we combine the technology acceptance model and consumer socialisation theory to explore the mediating role of trust in a rapidly expanding and growing industry sector. In surveying 150 Europeans to test our hypotheses around the aforementioned concepts, findings show that the perceived usefulness of a brand's social media is impacted by a set of atmospheric cues, and it influences the level of trust in both the fashion brand and its social media channels. Peer communication also influences perceived usefulness and level of trust in both the fashion brand and its social media channels. Trust in the brand but not its social media channels impacts purchase intention. The role of privacy concerns is limited in our model. We draw implications for theory around combining consumer socialisation theory and the technology acceptance model and for managers around parallel strategies to build different sets of trust on social media.

show abstract

What creates trust and who gets loyalty in social commerce?

Cited by 70 publications

References 58 publications

A Meta-Analytic Structural Equation Model for Understanding Social Commerce Adoption

A Meta-Analytic Structural Equation Model for Understanding Social Commerce Adoption

Understanding Consumers’ Purchase Intentions in Social Commerce through Social Capital: Evidence from SEM and fsQCA

How trust leads to online purchase intention founded in perceived usefulness and peer communication

Contact Info

Product

Resources

About