A Benchmark for Banks’ Strategy in Online Presence – An Innovative Approach Based on Elements of Search Engine Optimization (SEO) and Machine Learning Techniques
This paper aims to offer a new decision tool to assist banks in evaluating their efficiency of Internet presence and in planning the IT investments towards gaining better Internet popularity. The methodology used in this paper goes beyond the simple website interface analysis and uses web crawling as a source for collecting website performance data and employed web technologies and servers. The paper complements this technical perspective with a proposed scorecard used to assess the efforts of banks in Internet presence that reflects the banks’ commitment to Internet as a distribution channel. An innovative approach based on Machine Learning Techniques, the K-Nearest Neighbor Algorithm, is proposed by the author to estimate the Internet Popularity that a bank is likely to achieve based on its size and efforts in Internet presence.
Volume (Year): 14 (2011)
Issue (Month): 1 (June)
|Contact details of provider:|| Postal: 6 ROMANA PLACE, 70167 - BUCHAREST|
Web page: http://www.management.ase.ro/
More information through EDIRC
When requesting a correction, please mention this item's handle: RePEc:rom:econmn:v:14:y:2011:i:1:p:91-105. See general information about how to correct material in RePEc.
For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: (Ciocoiu Nadia Carmen)
If references are entirely missing, you can add them using this form.