This paper describes how to optimise the use of Internet search engines when investigating a document for possible non-original content. Services such as Turnitin do not guarantee to identify all non-original content, leading tutors to have to conduct manual searches when suspicion of non-originality remains. Previous studies have suggested that the investigator should manually select memorable phrases from the paper and submit them to a general search engine. The studies in this paper demonstrate that selecting phrases at random is just as effective. Several corpora of documents were obtained from a number of different academic areas, and several phrases were obtained from each. Strings, of increasing length starting with a single word, from these phrases were submitted to specialised and general search engines and the number of hits recorded. A common finding of these searches was that, in almost all cases, strings of six words were sufficiently distinct to uniquely identify the document that the string was taken from. One consequence of this is that totally automated tools are possible for this search-engine based non-originality detection technique.

Electronic marketplaces are the latest development in business-to-business electronic commerce. This paper describes research into the impact, and acceptance of fully-automated e-markets by potential users in the freight industry. The main finding of the research is that users would be nervous relinquishing total control to such systems from the outset. They would like to be able to develop a relationship with the system over time and, when trust has been established, to increase delegation and reduce their monitoring of the system.

Although there is conflicting advice as to the advisability of allowing students access to non-originality detection systems in advance of coursework submissions there appears to be no empirical evidence to support either position. This paper reports on an analysis of the pre-submissions and final reports of the final year dissertations of about 100 undergraduate BIT and Computing students. The interpretation of the results would suggest that there is no measurable impact upon student behaviour.