Access

You are not currently logged in.

Access your personal account or get JSTOR access through your library or other institution:

login

Log in to your personal account or through your institution.

If You Use a Screen Reader

This content is available through Read Online (Free) program, which relies on page scans. Since scans are not currently available to screen readers, please contact JSTOR User Support for access. We'll provide a PDF copy for your screen reader.

A Model of Web Site Browsing Behavior Estimated on Clickstream Data

Randolph E. Bucklin and Catarina Sismeiro
Journal of Marketing Research
Vol. 40, No. 3 (Aug., 2003), pp. 249-267
Stable URL: http://www.jstor.org/stable/30038857
Page Count: 19
  • Read Online (Free)
  • Download ($24.00)
  • Subscribe ($19.50)
  • Cite this Item
Since scans are not currently available to screen readers, please contact JSTOR User Support for access. We'll provide a PDF copy for your screen reader.
A Model of Web Site Browsing Behavior Estimated on Clickstream Data
Preview not available

Abstract

Using the clickstream data recorded in Web server log files, the authors develop and estimate a model of the browsing behavior of visitors to a Web site. Two basic aspects of browsing behavior are examined: (1) the visitor's decisions to continue browsing (by submitting an additional page request) or to exit the site and (2) the length of time spent viewing each page. The authors propose a type II tobit model that captures both aspects of browsing behavior and handles the limitations of server log-file data. The authors fit the model to the individual-level browsing decisions of a random sample of 5000 visitors to the Web site of an Internet automotive company. Empirical results show that visitors' propensity to continue browsing changes dynamically as a function of the depth of a given site visit and the number of repeat visits to the site. The dynamics are consistent both with "within-site lock-in" or site "stickiness" and with learning that carries over repeat visits. In particular, repeat visits lead to reduced page-view propensities but not to reduced page-view durations. The results also reveal browsing patterns that may reflect visitors' timesaving strategies. Finally, the authors report that simple site metrics computed at the aggregate level diverge substantially from individual-level modeling results, which indicates the need for Web site analyses to control for cross-sectional heterogeneity.

Page Thumbnails

  • Thumbnail: Page 
249
    249
  • Thumbnail: Page 
250
    250
  • Thumbnail: Page 
251
    251
  • Thumbnail: Page 
252
    252
  • Thumbnail: Page 
253
    253
  • Thumbnail: Page 
254
    254
  • Thumbnail: Page 
255
    255
  • Thumbnail: Page 
256
    256
  • Thumbnail: Page 
257
    257
  • Thumbnail: Page 
258
    258
  • Thumbnail: Page 
259
    259
  • Thumbnail: Page 
260
    260
  • Thumbnail: Page 
261
    261
  • Thumbnail: Page 
262
    262
  • Thumbnail: Page 
263
    263
  • Thumbnail: Page 
264
    264
  • Thumbnail: Page 
265
    265
  • Thumbnail: Page 
266
    266
  • Thumbnail: Page 
267
    267