To read the full version of this content please select one of the options below:

Using multistage competing risks approaches to model web page transitions

Patrick Mair (Harvard University, Cambridge, Massachusetts, USA)
Horst Treiblmaier (MODUL University Vienna, Vienna, Austria)
Paul Benjamin Lowry (Faculty of Business and Economics, The University of Hong Kong, China)

Internet Research

ISSN: 1066-2243

Article publication date: 5 June 2017

Abstract

Purpose

The purpose of this paper is to present competing risks models and show how dwell times can be applied to predict users’ online behavior. This information enables real-time personalization of web content.

Design/methodology/approach

This paper models transitions between pages based upon the dwell time of the initial state and then analyzes data from a web shop, illustrating how pages that are linked “compete” against each other. Relative risks for web page transitions are estimated based on the dwell time within a clickstream and survival analysis is used to predict clickstreams.

Findings

Using survival analysis and user dwell times allows for a detailed examination of transition behavior over time for different subgroups of internet users. Differences between buyers and non-buyers are shown.

Research limitations/implications

As opposed to other academic fields, survival analysis has only infrequently been used in internet-related research. This paper illustrates how a novel application of this method yields interesting insights into internet users’ online behavior.

Practical implications

A key goal of any online retailer is to increase their customer conversation rates. Using survival analysis, this paper shows how dwell-time information, which can be easily extracted from any server log file, can be used to predict user behavior in real time. Companies can apply this information to design websites that dynamically adjust to assumed user behavior.

Originality/value

The method shows novel clickstream analysis not previously demonstrated. Importantly, this can support the move from web analytics and “big data” from hype to reality.

Keywords

Acknowledgements

The authors would like to thank Marcus Hudec for his valuable methodological input at an early stage of this research project.

Citation

Mair, P., Treiblmaier, H. and Lowry, P.B. (2017), "Using multistage competing risks approaches to model web page transitions", Internet Research, Vol. 27 No. 3, pp. 650-669. https://doi.org/10.1108/IntR-06-2016-0167

Publisher

:

Emerald Publishing Limited

Copyright © 2017, Emerald Publishing Limited