Melbourne Business School - Research Publications

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Subject: Marketing × Start date: 2006 × End date: 2007 × Type: Journal Article × Author: DANAHER, PETER ×

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    Factors affecting Web site visit duration: A cross-domain analysis
    Danaher, PJ ; Mullarkey, GW ; Essegaier, S (SAGE PUBLICATIONS INC, 2006-05)
    In this study, the authors examine factors that affect Web site visit duration, including user demographics, text and graphics content, type of site, presence of functionality features, advertising content, and the number of previous visits. The authors use a random effects model to determine the impact of these factors on site duration and the number of pages viewed. The proposed method accounts for three distinct sources of heterogeneity that arise from differences among people, Web sites, and visit occasions to the same Web site by the same person. The model is fit using one month of user-centric panel data, and it encompasses the 50 most popular sites in a market. The results show that, in general, older people and women visit Web sites for a longer period. Some surprising results are revealed in an examination of interactions between these demographic and site characteristic variables. For example, sites with higher levels of advertising usually result in lower visit duration, but this is not the case for older people. The model also yields insights into the relative importance of different sources of heterogeneity in visit duration; heterogeneity in visit occasions dominates over individual-level and Web site-specific heterogeneity.
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    Modeling page views across multiple websites with an application to Internet reach and frequency prediction
    Danaher, PJ (INFORMS, 2007-05-01)
    In this study, we develop a multivariate generalization of the negative binomial distribution (NBD). This new model has potential application to situations where separate NBDs are correlated, such as for page views across multiple websites. In turn, our page view model is used to predict the audience for Internet advertising campaigns. For very large Internet advertising schedules, a simple approximation to the multivariate model is also derived. In a test of nearly 3,000 Internet advertising schedules, the two new models are compared with some proprietary and nonproprietary models previously used for Internet advertising and are shown to be significantly more accurate.