Efficiency analysis of forestry journals:suggestions for improving journals' quality

In this paper we attempt to assess the impact of journals in the field of forestry, in terms of bibliometric data, by providing an evaluation of forestry journals based on data envelopment analysis (DEA). In addition, based on the results of the conducted analysis, we provide suggestions for improving the impact of the journals in terms of widely accepted measures of journal citation impact, such as the journal impact factor (IF) and the journal h-index. More specifically, by modifying certain inputs associated with the productivity of forestry journals, we have illustrated how this method could be utilized to raise their efficiency, which in terms of research impact can then be translated into an increase of their bibliometric indices, such as the h-index, IF or eigenfactor score. © 2013 Elsevier Ltd.

A comparison of the impact of avoidance cues in hazard avoidance during evaluation of text entry

The research presented in this paper is part of an ongoing investigation into how best to support meaningful lab-based evaluations of mobile technologies. In our previous work, we developed a hazard avoidance system for use during lab evaluations [1]; in the work reported here, we further assess the impact of this system, specifically in terms of the effect of avoidance cue type on speech-based text entry tasks.