Beyond Distributed Cognition

Widening Our Conceptual Foundations to better support virtual organization
  • Michael D. Cohen
Part of the IFIP International Federation for Information Processing book series (IFIPAICT, volume 236)


American social science since World War II has been centrally shaped by the “cognitive revolution.” Fields as disparate as behavioral economics and cognitive anthropology have exploited a shared core of ideas about the workings and limitations of human cognition, such short-term memory and judgment heuristics. This cognitive toolkit has been a principal asset in the efforts to understand and better support the requirements of newly emerging forms of virtual organization. This keynote address examines two other human faculties, habit and emotion. Across western intellectual history these have often been understood as equally important determinants of organized action, and this was the case in the period before World War II. However, since then habit and emotion have not been tightly integrated dimensions of our analyses of social life, including virtual organizing. Rather they have served, if present at all, as labels for clusters of exceptions, cases that involved issues not well handled by the default cognitive approach. Both habit and emotion are rising in psychology as topics of inquiry. These two additional human faculties are notable for being significantly less available to direct introspection, but powerful new measurement techniques—most notably various forms of scanning—are bringing into focus their large role in determining our actions. The keynote provides an overview of these developments and some suggestions some of their implications for the understanding and supporting virtual organizing with concepts that make habit and emotion more central to the primary analysis.


Behavioral Economic Virtual Organization Keynote Address Human Faculty Shared Core 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

Copyright information

© International Federation for Information Processing 2007

Authors and Affiliations

  • Michael D. Cohen
    • 1
  1. 1.School of InformationUniversity of MichiganAnn ArborUSA

Personalised recommendations