Using organisational information processing maturity as a predictor of information technology adoption

James E. Yao, Zhongxian Wang, Ruben Xing, June Lu and Xiaohe Xu

International Journal of Information and Decision Sciences, 2008, vol. 1, issue 2, 221-233

Abstract: Asynchronous transfer mode (ATM) is a switching and multiplexing mechanism operating over a fibre-based physical network. It can be used to provide virtual private network services to businesses. Today, ATM services represent a billion-dollar business around the world. The adoption of ATM technology will probably change the current networking systems, upgrade the quality of current networks and provide increased services. Despite the increasing deployment of ATM technology and the important role it plays in today's information technology infrastructure, little research has been found to its study with respect to social sciences. The present study examined information processing maturity and its relationship with the adoption of ATM technology in organisations. Research results provided strong evidence that there is a statistically significant relationship between organisational information processing maturity and ATM adoption in organisations.

Keywords: ATM adoption; asynchronous transfer mode; IT adoption; information technology; information processing maturity; information systems; social sciences. (search for similar items in EconPapers)
Date: 2008
References: Add references at CitEc
Citations:

Downloads: (external link)
http://www.inderscience.com/link.php?id=22296 (text/html)
Access to full text is restricted to subscribers.

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:ids:ijidsc:v:1:y:2008:i:2:p:221-233

Access Statistics for this article

More articles in International Journal of Information and Decision Sciences from Inderscience Enterprises Ltd
Bibliographic data for series maintained by Sarah Parker ().