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highway can help reduce cost, effort, and time. Yet the development of intelligent
agents is still in its infancy. As they gain in popularity and use, we can expect to see
more sophisticated and better-developed intelligent agents.
Information studies research has studied information seeking behavior for over fi ve
decades now and this research can serve as an excellent theoretical basis for the study
of the Internet as an information source and intelligent agents as mediators in this
digital environment (e.g., Kulthau 1991 , 1993 ; Rasmussen, Pejtersen, and Goodstein
1994 ; Spink 1997 , Wilson 1981 , 1994 1999). Detlor (2003) used a case study to explore
how knowledge workers made use of Internet-based information systems and found
that information studies theory provides an appropriate framework for examining
Internet-based information seeking behaviors. Detlor, Sproule, and Gupta (2003) made
use of a similar conceptual framework to explore goal-directed behavior in online
shopping environments. Choo, Detlor, and Turnbull (2000a ) investigated how knowl-
edge workers use the web to fi nd information external to their organizations as part
of their daily work life. A typology of different complementary modes of using the
web as an information source was identifi ed and described (e.g., formal search, infor-
mal search).
Detlor (2004) adopted an information vantage point that views enterprise knowl-
edge portals as more than tools to merely deliver content. He instead see them as
shared workspaces that can facilitate communication and collaboration among knowl-
edge workers. Intelligent agents can play a signifi cant role to improve the interaction
between knowledge workers and knowledge portals for the successful completion of
everyday work tasks. Empirical research studies on information seeking helps defi ne
a web use model based on information seeking motives and modes. The advantage of
using a theoretical framework as a starting point is that online behavior and prefer-
ences can be better understood, explained, and predicted. These online behavioral
preferences can then be used to better design both online environments and mediators
such as intelligent agents.

Adaptive Technologies
Adaptive technologies are used to better target content to a specifi c knowledge worker
or to a specifi c group of knowledge workers who share common work needs. Custom-
ization refers to the knowledge worker manually changing their knowledge environ-
ment. For example, selecting user preferences to change the desktop interface,
specifying certain requirements in content to be provided to them (language, format),
or subscribing to certain news or listserv services.