This Article Full Text (PDF) References Alert me when this article is cited Alert me if a correction is posted Services Email this article to a friend Similar articles in this journal Alert me to new issues of the journal Download to citation manager Citing Articles Citing Articles via Google Scholar Google Scholar Articles by Hui, S. K. Articles by Bradlow, E. T. Search for Related Content

Path Data in Marketing: An Integrative Framework and Prospectus for Model Building

Stern School of Business, New York University, New York, New York 10012
The Wharton School of the University of Pennsylvania, Philadelphia, Pennsylvania 19104
The Wharton School of the University of Pennsylvania, Philadelphia, Pennsylvania 19104
khui{at}stern.nyu.edu
faderp{at}wharton.upenn.edu
ebradlow{at}wharton.upenn.edu

Many data sets, from different and seemingly unrelated marketing domains, all involve paths—records of consumers' movements in a spatial configuration. Path data contain valuable information for marketing researchers because they describe how consumers interact with their environment and make dynamic choices. As data collection technologies improve and researchers continue to ask deeper questions about consumers' motivations and behaviors, path data sets will become more common and will play a more central role in marketing research.

To guide future research in this area, we review the previous literature, propose a formal definition of a path (in a marketing context), and derive a unifying framework that allows us to classify different kinds of paths. We identify and discuss two primary dimensions (characteristics of the spatial configuration and the agent) as well as six underlying subdimensions. Based on this framework, we cover a range of important operational issues that should be taken into account as researchers begin to build formal models of path-related phenomena. We close with a brief look into the future of path-based models, and a call for researchers to address some of these emerging issues.

Key Words: path data; path models; integrative review; grocery shopping; eye tracking; Web browsing; clickstream; information acceleration
History: Received: February 9, 2007; accepted: February 27, 2008.