Author
Listed:
- Chun-T’ing Loh
(Universiti Tunku Abdul Rahman, Faculty of Business and Finance)
- Ah-Suat Lee
(Universiti Tunku Abdul Rahman, Faculty of Business and Finance)
- Yoon-Mei Chin
(Universiti Tunku Abdul Rahman, Faculty of Business and Finance)
- Yen-Hong Ng
(Universiti Tunku Abdul Rahman, Faculty of Business and Finance)
- Pik-Yin Foo
(Universiti Tunku Abdul Rahman, Faculty of Business and Finance)
- Zam Zuriyati Mohamad
(Universiti Tunku Abdul Rahman, Faculty of Business and Finance)
Abstract
This study proposes a framework that aims to identify the degree and nature of self-regulation when assessing, consuming and sharing networked content and to determine the factors included by users when self-regulating, mediating or controlling the use of networked media contents. In addition, this study aims to examine the users’ awareness, readiness and expectation on being subject to the Content Code. Based on the Theory of Self-Regulation and Theory of Planned Behaviour, this study conceptualises that trust, subjective norms and emotion will contribute to networked content self-regulation and thereafter lead to intention to adopt the content code. In order to achieve the objectives of this study, a quantitative, cross-sectional research design will be applied by distributing questionnaire to the network users, aged 20 to 39 in rural and urban areas from 4 regions in Malaysia. The data collected will be analysed using Partial Least Square Structural Equation Modelling. It is expected this study will be beneficial specifically to the Content Regulation Consumer and Industry Affairs Division, Malaysian, Communication and Multimedia Commission on the public readiness to being subject to the Content Code. Generally, this study will be beneficial to the public in promoting awareness on self-regulation and content code.
Suggested Citation
Chun-T’ing Loh & Ah-Suat Lee & Yoon-Mei Chin & Yen-Hong Ng & Pik-Yin Foo & Zam Zuriyati Mohamad, 2023.
"Practice of Networked Content Self-regulation Amongst Malaysian Users,"
Advances in Economics, Business and Management Research, in: Fanyu Chen & Keng Soon William Choo & Voon Hsien Lee & Chooi Yi Wei (ed.), Proceedings of the 10th International Conference on Business, Accounting, Finance and Economics (BAFE 2022), pages 463-476,
Springer.
Handle:
RePEc:spr:advbcp:978-2-494069-99-2_34
DOI: 10.2991/978-2-494069-99-2_34
Download full text from publisher
To our knowledge, this item is not available for
download. To find whether it is available, there are three
options:
1. Check below whether another version of this item is available online.
2. Check on the provider's
web page
whether it is in fact available.
3. Perform a
for a similarly titled item that would be
available.
Corrections
All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:spr:advbcp:978-2-494069-99-2_34. See general information about how to correct material in RePEc.
If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.
We have no bibliographic references for this item. You can help adding them by using this form .
If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.
For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Sonal Shukla or Springer Nature Abstracting and Indexing (email available below). General contact details of provider: http://www.springer.com .
Please note that corrections may take a couple of weeks to filter through
the various RePEc services.