Disclosing too much? Situational factors affecting information disclosure in social commerce environment

Sharma, Shwadhin; Crossler, Robert E.

doi:10.1016/j.elerap.2014.06.007

Cited by 149 publications

(112 citation statements)

References 82 publications

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“…Recent studies have emphasized that consumers' privacy concern and perceived risk towards social networking sites has been found to be negatively related to their intentions to share information and purchase a product (Featherman & Hajli, 2015;Sharma & Crossler, 2014). It is necessary to conduct a more comprehensive study concentrating on other factors that may play an enabling, moderating or mediating role to affect consumers' social interactions.…”

Section: Limitations and Suggestions For Future Researchmentioning

confidence: 96%

“…Please indicate the extent to which you agree or disagree with each statement by ticking the appropriate number. Intention of purchase (Noh et al, 2013;Sharma & Crossler, 2014) 1. I am likely to provide my personal information to purchase on social commerce sites.…”

Section: Appendix B Measure and Itemsmentioning

confidence: 99%

“…We developed a new three-item scale based on those used in previous studies (Chen et al, 2011;Cheung et al, 2014;Wang & Chiang, 2009) since there was no previously existing scale. The four-item scale for the intention to purchase was modified from Noh et al (2013) and Sharma and Crossler (2014) to fit our research context.…”

Section: Measurementsmentioning

confidence: 99%

See 2 more Smart Citations

Social interaction-based consumer decision-making model in social commerce: The role of word of mouth and observational learning

Wang

2017

International Journal of Information Management

284

220

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Section: Limitations and Suggestions For Future Researchmentioning

confidence: 96%

Section: Appendix B Measure and Itemsmentioning

confidence: 99%

See 1 more Smart Citation

Social interaction-based consumer decision-making model in social commerce: The role of word of mouth and observational learning

Wang

2017

International Journal of Information Management

284

220

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“…Otherwise, the technology would not be accepted (Li et al, 2014). Since the perceived benefit of adopting healthcare wearable device has been measured by perceived expectancy and hedonic motivation (Sharma and Crossler, 2014), we only need to consider the effect of perceived privacy risk in determining consumer's adoption intention. Consistent with prior studies about privacy calculus, we hypothesize that H9.…”

Section: Privacy Perspectivementioning

confidence: 99%

An empirical study of wearable technology acceptance in healthcare

Gao

Yan

2015

Industrial Management &Amp; Data Systems

522

507

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Access to this document was granted through an Emerald subscription provided by emerald-srm:123705 [] For AuthorsIf you would like to write for this, or any other Emerald publication, then please use our Emerald for Authors service information about how to choose which publication to write for and submission guidelines are available for all. Please visit www.emeraldinsight.com/authors for more information. About Emerald www.emeraldinsight.comEmerald is a global publisher linking research and practice to the benefit of society. The company manages a portfolio of more than 290 journals and over 2,350 books and book series volumes, as well as providing an extensive range of online products and additional customer resources and services.Emerald is both COUNTER 4 and TRANSFER compliant. The organization is a partner of the Committee on Publication Ethics (COPE) and also works with Portico and the LOCKSS initiative for digital archive preservation. AbstractPurpose: The purpose of this paper is to investigate the factors associated with consumer's intention to adopt wearable technology in healthcare, and to examine the moderating effects of product type on consumer's adoption intention.Design/methodology/approach: An integrated acceptance model was developed based on unified theory of acceptance and use of technology 2 (UTAUT2), protection motivation theory (PMT), and privacy calculus theory. The model was tested with 462 respondents using a survey.Findings: Consumer's decision to adopt healthcare wearable technology is affected by factors from technology, health, and privacy perspectives. Specially, fitness device users care more about hedonic motivation, functional congruence, social influence, perceived privacy risk, and perceived vulnerability, but medical device users pay more attention to perceived expectancy, self-efficacy, effort expectancy, and perceived severity.Originality/value: This study is among the first to investigate healthcare wearable device from behavioral perspective. It also helps to comprehensively understand emerging health information technology (HIT) acceptance from technology, health, and privacy perspectives.

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“…Social networking is a relatively a new phenomenon and opened unparalleled opportunities for individuals to engage online (Sharma & Crossler, 2014). These unprecedented levels of engagement include the use of social networking sites (SNS) in educational settings.…”

Section: Student Use Of Social Networkingmentioning

confidence: 99%

Purpose of social networking use and victimisation: Are there any differences between university students and those not in HE?

Benson

Saridakis

Tennakoon

2015

Computers in Human Behavior

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Disclosing too much? Situational factors affecting information disclosure in social commerce environment

Cited by 149 publications

References 82 publications

Social interaction-based consumer decision-making model in social commerce: The role of word of mouth and observational learning

Social interaction-based consumer decision-making model in social commerce: The role of word of mouth and observational learning

An empirical study of wearable technology acceptance in healthcare

Purpose of social networking use and victimisation: Are there any differences between university students and those not in HE?

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