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Endnotes
1 See also Grönlund (2004), Andersen and Heinriksen (2005), and Titah and Barki (2006).
2 We would also like to thank Prof. Ronnie L. Korosec, University of Central Florida, who as part of an e-government research project on which she is working with Prof.
Norris, identified four empirical articles that our search missed.
3 For a definition of empirical, see Merriam-Webster Online at http://www.m-w.com/
cgi-bin/dictionary?book=Dictionary&va=empirical&x=17&y=15 retrieved April 26, 2005.
4 We categorized these journals as either from the social sciences or information sys- tems and technology based on their titles and typical contents. Other scholars might categorize them somewhat differently.
The Scholarly Lterature on E-Government
5 There is a story (no doubt, apocryphal) about an introductory statistics course in which the instructor assigned students the task of correlating the incidence of traffic accidents with the occurrence of high tide. The students found that there was a high correlation; when high tide occurred, more traffic accidents occurred. The instructor’s point was twofold: 1) Correlation does not equal causation (high tide occurred during rush hour!); and 2) some variables ought not to be correlated at all (it makes no sense to do so).
This work was previously published in International Journal of Electronic Government Research, Vol. 2, Issue 4, edited by D. F. Norris, pp. 40-56, copyright 2006 by IGI Publishing, formerly known as Idea Group Publishing (an imprint of IGI Global).
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