Information Foraging—A Model for Exploration Breadth and Depth

ABSTRACT

The optimal path choice theory from biology implies that foragers should evaluate all sites before selecting something feasible when site relocation costs are low and there are few sites to explore. In internet information foraging, although the cost of moving to another site is negligible, the number of relevant sites can be large and exploration costs vary. We examine human internet information foraging behaviors and propose a model relating them to established cognitive measures.

KEYWORDS:

• Information foraging
• web exploration
• search depth and breadth

Acknowledgments

We would like to express special thanks to our anonymous reviewers and the senior editor whose suggestions helped improve our article.

Future research areas

Forthcoming research should focus on extending these findings to other products, such as tangible goods, instead of services. Our results could also be extended with research from an economics perspective looking at how people with lower income may act differently than those with higher income (who may value time differently) to acquire a product and how that interplays with the cost of the product.

Additional information

Notes on contributors

Bjarne Berg

Bjarne Berg is a professor of computer science and mathematics at Lenoir Rhyne University and the leader of Advanced Tax Analytics and Innovation at PwC. He is a frequent speaker at Business Intelligence (BI) conferences worldwide and wrote five books on BI and data warehousing. He has over 25 years of management consulting experience and previously was Sr. Partner and global practice leader at Comerit Inc., BI practice leader at VIP and Sr. Manager in PwC’s global data warehouse group. Berg holds a BS (Appalachian State University), an MBA (East Carolina University), a DBA (University of Sarasota), and a PhD (University of North Carolina).

Antonis C. Stylianou

Antonis Stylianou is the BISOM Department Chair and professor of MIS and Data Science and Business Analytics at UNC Charlotte. Stylianou has published numerous research articles in Management Science, EJIS, JAIS, Decision Sciences, DSS, I&M, IJEC, CACM, and other journals. He has received funding from the NSF, the U.S. DoE, the NIST, and other sources. In addition to UNC Charlotte, he has taught courses and seminars at Kent State University, Villanova University, Mannheim University (Germany), Cologne University (Germany), and EGADE (Technologico de Monterrey, Mexico). He currently serves as senior editor for the Database for Advances in Information Systems journal.

Razvan A. Mezei

Razvan A. Mezei is currently a software developer at Epic Systems Corporation and has previously worked as an assistant professor at Lenoir Rhyne University and at Lander University. He has authored or coauthored several research articles, two books, and a monograph. Mezei holds a BS (in Mathematics & Computer Science, University of Oradea), a MS (in Computer Science, University of Oradea), a MS (in Mathematics, University of Memphis), a MS (in Statistics, University of Memphis), a MS (in Online Teaching and Instructional Design, Lenoir-Rhyne University), and a PhD (Mathematics, University of Memphis).