The implications of usage statistics as an economic factor in scholarly communications

Usage statistics for electronic resources are needed, and highly desirable, for many reasons. It is encouraging to see the beginnings of quality, reliable usage data. This data can form the basis of economic decisions (selection and cancellation) that make a great deal of sense in the context of the individual library. However, the cumulative effects of such decisions could have serious implications for scholarly communications. For example, the journals of small research communities could easily be vulnerable to mass cancellations, and might fold. Fortunately, open access provides an alternative. The question of whether the impact of local decisions on scholarly communications as a whole should be taken into account in collection development policies is raised. The possibility that usage statistics could form the basis for a usage-based pricing system is discussed, and found to be highly inadvisable, as usage-based pricing tends to discourage usage

Useful academic references for data mining and usage statistics

Relates to the following software for analysing Blackboard stats http://www.edshare.soton.ac.uk/11134/ Is supporting material for the following podcast: http://youtu.be/yHxCzjiYBo

Novità recenti dal mondo delle statistiche di uso: il protocollo SUSHI e le nuove linee guida dell’ICOLC

E-measures are becoming increasingly essential for digital libraries management. The article deals with the mainfold problems correlated with usage statistics and discuss the new NISO/SUSHI (Standardized Usage Statistics Harvesting Initiative)Initiative, the protocol to harvest usage statistics in automated way and the Revised guidelines for statistical measures of usage of web-based information resources of ICOLC

My repository is being aggregated: a blessing or a curse?

Usage statistics are frequently used by repositories to justify their value to the management who decide about the funding to support the repository infrastructure. Another reason for collecting usage statistics at repositories is the increased use of webometrics in the process of assessing the impact of publications and researchers. Consequently, one of the worries repositories sometimes have about their content being aggregated is that they feel aggregations have a detrimental effect on the accuracy of statistics they collect. They believe that this potential decrease in reported usage can negatively influence the funding provided by their own institutions. This raises the fundamental question of whether repositories should allow aggregators to harvest their metadata and content. In this paper, we discuss the benefits of allowing content aggregations harvest repository content and investigate how to overcome the drawbacks

A simple recipe for making accurate parametric inference in finite sample

Constructing tests or confidence regions that control over the error rates in the long-run is probably one of the most important problem in statistics. Yet, the theoretical justification for most methods in statistics is asymptotic. The bootstrap for example, despite its simplicity and its widespread usage, is an asymptotic method. There are in general no claim about the exactness of inferential procedures in finite sample. In this paper, we propose an alternative to the parametric bootstrap. We setup general conditions to demonstrate theoretically that accurate inference can be claimed in finite sample

Motor Vehicle Usage Patterns in Australia: A Comparative Analysis of Driver, Vehicle & Purpose Characteristics for Household & Freight Travel

An ordered probit model is used to predict motor vehicle usage in Australia on the basis of the unit record files underlying the Australian Bureau of Statistics’ Survey of Motor Vehicle Use. Both household and freight transport are analysed. The paper examines the statistical significance of a number of driver, vehicle and travel purpose variables on the level of motor vehicle usage. Factors analysed include driver age and gender, vehicle and fuel type, age of the vehicle, purpose of trip, place of registration, type of freight and number of drivers. The results indicate that the cut-off points between very low, low, medium, high and very high vehicle usages are significant and that the factors associated with differences in usage include driver age, engine size and age of vehicle for household vehicles and the type of freight, type of vehicle, gender and number of drivers for freight usage

Beyond Description: Converting Web Site Usage Statistics into Concrete Site Improvement Ideas

Web site usage statistics are a widely used tool for Web site development, but libraries are still learning how to use them successfully. This case study summarizes how Morris Library at Southern Illinois University Carbondale implemented Google Analytics on its Web site and used the reports to inform a site redesign. As the main campus library at a research university with about 20,000 undergraduate and graduate students, the library included resources from multiple library departments on a single site. In planning the redesign, Morris Library\u27s Virtual Library Group combined usage reports with information from other sources, such as usability tests and user comments. The Virtual Library Group faced barriers to interpreting and applying the usage statistics in the site redesign, including some that were specific to the library\u27s implementation of the Google Analytics tool and some limitations inherent with Web usage statistics in general. Some key barriers in applying the usage statistics to a redesign included sifting through data that did not have implications for the site redesign, interpreting the implications of usage numbers for the site redesign, and balancing competing interests within the library. Nevertheless, the usage statistics enabled the Virtual Library Group to make better decisions by providing a source of factual information about the site\u27s use rather than relying on staff members’ opinions and conjectures