Location via proxy:   [ UP ]  
[Report a bug]   [Manage cookies]                
skip to main content
10.1145/3414752.3414794acmotherconferencesArticle/Chapter ViewAbstractPublication PagesicemeConference Proceedingsconference-collections
research-article

The Effect of Information Sharing Intention on Virtual Communities in China: An Empirical Study

Published: 18 November 2020 Publication History

Abstract

With the rapid development of information technology, various virtual communities like WeChat have sprung up in China. Based on Technology Acceptance Model (TAM) and theory of perceived value, the paper takes the “Top Stories” function of WeChat as an example and contributes to discuss what factors mainly affect users’ information sharing intention. Results with 250 valid user data indicate that content quality and social image both positively influence perceived usefulness. Besides, perceived usefulness, perceived entertainment and perceived ease of use have a noticeable positive effect on perceived value while privacy anxiety negatively affects it. However, the impact of perceived responsibility on perceived value is not significant. Finally, perceived value plays a crucial role in users’ information sharing intention. Generally, the findings have theoretical and practical value on improving the operational efficiency of the “Top Stories” function and informational communication in the virtual environment.

References

[1]
China Internet Network Information Center. 2019. The 44th China Statistical Report on Internet Development. DOI= http://www.cnnic.net.cn/hlwfzyj/hlwxzbg/hlwtjbg/201908/t20190830_70800.htm.
[2]
Davis, F. D. 1989. Perceived usefulness, perceived ease of use, and user acceptance of information technology. MIS Quarterly. 13 (Sept.1989), 319-340.
[3]
Zeithaml, V. A. 1988. Consumer perceptions of price, quality, and value: A means-end model and synthesis of evidence. Journal of Marketing. 52 (Jul. 1988), 2-22.
[4]
Guo, Q., Johnson, C. A., Unger, J. B. 2007. Utility of the theory of reasoned action and theory of planned behavior for predicting Chinese adolescent smoking. Addictive Behaviors. 32 (May. 2007), 1066-1081.
[5]
Morris, M. G., and Venkatesh, V. 2006. Age differences in technology adoption decisions: Implications for a changing work force. Personnel Psychology. 52 (Dec. 2006), 375-403.
[6]
Pavlou, P. A., and Fygenson, M. 2006. Understanding and predicting electronic commerce adoption: An extension of the theory of planned behavior. MIS Quarterly. 30 (Mar. 2006), 115-143.
[7]
Gan, C., and Wang, W. 2015. Uses and gratifications of social media: A comparison of microblog and WeChat. Journal of Systems and Information Technology. 17 (Nov. 2015), 351-363.
[8]
Lin, K. 2011. E-Learning continuance intention: moderating effects of user e-Learning experience. Computers & Education. 56 (Feb. 2011), 515-526.
[9]
Ning, L., Zhang, X., and Liu, Z. 2013. Effects of interpersonal interaction on users’ continuance intention in social networking service. Journal of Beijing University of Posts and Telecommunications. 15 (Jun. 2013), 8-14. (in Chinese)
[10]
Kim, B., and Oh, J. 2011. The difference of determinants of acceptance and continuance of mobile data services: A value perspective. Expert Systems with Applications. 38 (Mar. 2011), 1798-1804.
[11]
Dabholkar, P. A. 1996. Consumer evaluations of new technology-based self-service options: An investigation of alternative models of service quality. International Journal of Research in Marketing. 13 (Feb. 1996), 29-51.
[12]
Tang, L., and Deng, S. 2012. The empirical research on the influencing factors of SNC users’ loyalty. Intelligence, Information and Sharing. 1 (Jan. 2012), 102-108.
[13]
Abdullah, F., and Ward, R. 2016. Developing a general extended technology acceptance model for E-Learning (GETAMEL) by analysing commonly used external factors. Computers in Human Behavior. 56, 238-256.
[14]
Fogel, J., and Nehmad, E. 2009. Internet social network communities: Risk taking, trust, and privacy concerns. Computers in Human Behavior. 25 (Jan. 2009), 153-160.
[15]
Erlandsson, A. 2015. Underlying psychological mechanisms of helping effects: Examining the when× why of charitable giving. Lund University.
[16]
Kuo, Y. F., Wu C. M., and Deng, W. J. 2009. The relationships among service quality, perceived value, customer satisfaction, and post-purchase intention in mobile value-added services. Computers in Human Behavior. 25 (Jul. 2009), 887-896.
[17]
Maltz, E. 2000. Is all communication created equal?: An investigation into the effects of communication mode on perceived information quality. Journal of Product Innovation Management. 17 (Mar. 2000), 110-127.
[18]
Sweeney, R. J., and Hsu, W. 2003. System and method for classifying cardiac depolarization complexes with multi-dimensional correlation. U.S. Patent. 6526313 B2 (Feb. 2003).
[19]
Venkatesh, V., and Davis, F. D. 1996. A model of the antecedents of perceived ease of use: Development and test. Decision Sciences. 27 (Sept. 1996), 451-481.
[20]
Bhattacherjee, A. 2001. Understanding information systems continuance: An expectation-confirmation model. MIS Quarterly. 25 (Sept. 2001), 351-370.
[21]
Kankanhalli, A., Tan, B. C., Wei, K. K., 2004. Cross-cultural differences and information systems developer values. Decision Support Systems. 38 (Nov. 2004), 183-195.
[22]
Malhotra, N. K., Kim, S. S., and Agarwal, J. 2003. Internet users' information privacy concerns (IUIPC): The construct, the scale, and a causal model. Information Systems Research. 38 (Aug. 2003), 183-195.
[23]
Erlandsson, A., Björklund, F., and Bäckström, M. 2015. Emotional reactions, perceived impact and perceived responsibility mediate the identifiable victim effect, proportion dominance effect and in-group effect respectively. Organizational Behavior and Human Decision Processes. 127 (Mar. 2015), 1-14.
[24]
Chen, C. J., and Hung, S. W. 2010. To give or to receive? Factors influencing members’ knowledge sharing and community promotion in professional virtual communities. Information & Management. 47 (May 2010), 226-236.
[25]
Fornell, C., and Larcker, D. F. 1981. Evaluating structural equation models with unobservable variables and measurement error. Journal of Marketing Research. 18 (Aug. 1981), 39-50.
[26]
Bagozzi, R. P., and Yi, Y. 1988. On the evaluation of structural equation models. Journal of the Academy of Marketing Science. 16 (Mar. 1988), 74-94.
[27]
Scott, J. E. 1995. The measurement of information systems effectiveness: Evaluating a measuring instrument, ACM SIGMIS Database: the DATABASE for Advances in Information Systems. 26 (Feb. 1995), 43-61.

Recommendations

Comments

Information & Contributors

Information

Published In

cover image ACM Other conferences
ICEME '20: Proceedings of the 2020 11th International Conference on E-business, Management and Economics
July 2020
312 pages
ISBN:9781450388016
DOI:10.1145/3414752
Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

Publisher

Association for Computing Machinery

New York, NY, United States

Publication History

Published: 18 November 2020

Permissions

Request permissions for this article.

Check for updates

Author Tags

  1. “Top Stories” function
  2. Information sharing intention
  3. Virtual communities
  4. WeChat

Qualifiers

  • Research-article
  • Research
  • Refereed limited

Conference

ICEME '20

Contributors

Other Metrics

Bibliometrics & Citations

Bibliometrics

Article Metrics

  • 0
    Total Citations
  • 63
    Total Downloads
  • Downloads (Last 12 months)5
  • Downloads (Last 6 weeks)2
Reflects downloads up to 13 Jan 2025

Other Metrics

Citations

View Options

Login options

View options

PDF

View or Download as a PDF file.

PDF

eReader

View online with eReader.

eReader

HTML Format

View this article in HTML Format.

HTML Format

Media

Figures

Other

Tables

Share

Share

Share this Publication link

Share on social media