The Stability of Self-Organized Rule-Following Work Teams

  • Authors:

  • Crayton C. Walker;Kevin J. Dooley

  • Affiliations:

  • Department of Operations and Information Management, University of Connecticut, Storrs, CT 06269. walker@uconnvm.uconn.edu;Departments of Management and Industrial & Management Systems Engineering, Arizona State University, Tempe, AZ 85287. kevin.dooley@asu.edu

  • Venue:
  • Computational & Mathematical Organization Theory
  • Year:
  • 1999

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Abstract

Self-organized rule-following systems are increasinglyrelevant objects of study in organization theory due to such systems‘capacity to maintain control while enabling decentralization ofauthority. This paper proposes a network model for such systems andexamines the stability of the networks‘ repetitive behavior. Thenetworks examined are Ashby nets, a fundamental class of binarysystems: connected aggregates of nodes that individually compute aninteraction rule, a binary function of their three inputs. Thenodes, which we interpret as workers in a work team, have two networkinputs and one self-input. All workers in a given team follow thesame interaction rule.We operationalize the notion of stability of the team‘s workroutine and determine stability under small perturbations for allpossible rules these teams can follow. To study the organizationalconcomitants of stability, we characterize the rules by their memory,fluency, homogeneity, and autonomy. We relate these measures to workroutine stability, and find that stability in ten member teams isenhanced by rules that have low memory, high homogeneity, and lowautonomy.