Hostname: page-component-586b7cd67f-r5fsc Total loading time: 0 Render date: 2024-11-23T16:44:18.706Z Has data issue: false hasContentIssue false
  • English
  • Français

A proposed improvement to the multilevel theory for hierarchical decision-making teams

Published online by Cambridge University Press:  02 February 2015

Mincheol Kang
Mincheol Kang*
Affiliation:
Division of e-Business, School of Business Administration, Ajou University, Suwon, Republic of Korea
Get access Rights & Permissions [Opens in a new window]

Abstract

The multilevel theory proposed by Hollenbeck et al. identified a set of core variables that are central to accuracy in decision-making in hierarchical teams with distributed expertise. Following the identification of the limitations of the original core variables, a new set of core variables is proposed: (a) member validity, which represents the overall predictability of team members with regard to the correct decision and (b) hierarchical sensitivity, which represents the effectiveness of the leader's weightings of members' recommendations. To test the revised theory, a computational model called Team-Soar is used. The simulation results show that the small set of new core variables explains a large portion of the variance in the team decision accuracy and mediates the effects of other variables on the accuracy. The revised theory can be used as a conceptual vehicle to parsimoniously explain the performance of hierarchical decision-making teams. The theory could also be used to diagnose and train real teams in terms of the core variables.

Keywords

multilevel theoryteam decision-makinghierarchical teamsimulation experimentcomputational test bedTeam-Soar
Type
Research Article
Information
Journal of Management & Organization , Volume 16 , Issue 1 , March 2010 , pp. 151 - 167
Copyright
Copyright © Cambridge University Press and Australian and New Zealand Academy of Management 2010

Access options

Get access to the full version of this content by using one of the access options below. (Log in options will check for institutional or personal access. Content may require purchase if you do not have access.)

References

Bandura, A (1977) Self-efficacy: Toward a unifying theory of behavioral change, Psychological Bulletin 84:191–215.Google Scholar
Brehmer, B and Hagafors, R (1986) Use of experts in complex decision making: A paradigm for the study of staff work, Organizational Behavior and Human Decision Processes 38:181–195.10.1016/0749-5978(86)90015-4Google Scholar
Brunswik, E (1955) Representative design and probabilistic theory in a functional psychology, Psychological Review 62:193–217.10.1037/h0047470Google Scholar
Cannon-Bowers, JA, Salas, E and Converse, S (1993) Shared Mental Models in Expert Team Decision Making, in Castellan, NJ Jr. (ed.) Individual and group decision making: Current issues, pp 221–245, Erlbaum, Hillsdale NJ.Google Scholar
Carley, KM and Prietula, MJ (1994) Computational organization theory – An introduction, in Carley, KM and Prietula, MJ (eds.) Computational Organization Theory, pp xi–xvii, Erlbaum, Hillsdale NJ.Google Scholar
Fleishman, EA and Zaccaro, SJ (1992) Toward a taxonomy of team performance functions, in Swezey, RW and Salas, E (eds.) Teams: Their Training and Performance, pp 31–56, Ablex, Norwood NJ.Google Scholar
Gigone, D and Hastie, R (1997) Proper analysis of the accuracy of group judgments, Psychological Bulletin 121:149–167.10.1037/0033-2909.121.1.149Google Scholar
Harvey, N, Harries, C and Fischer, I (2000) Using advice and assessing its quality, Organizational Behavior and Human Decision Processes 81: 252–273.10.1006/obhd.1999.2874Google Scholar
Hedlund, J, Ilgen, DR and Hollenbeck, JR (1998) Decision accuracy in computer-mediated versus face-to-face decision-making teams, Organizational Behavior and Human Decision Processes 76(1:30–47.10.1006/obhd.1998.2796Google Scholar
Hollenbeck, JR, DeRue, DS and Guzzo, R (2004) Bridging the gap between I/O research and HR practice: Improving team composition, team training, and team task design, Human Resource Management 43(4:353–366.10.1002/hrm.20029Google Scholar
Hollenbeck, JR, Ilgen, DR, LePine, JA, Colquitt, JA and Hedlund, J (1998a) Extending the multilevel theory of team decision making: Effects of feedback and experience in hierarchical teams, Academy of Management Journal 41(3:269–283.Google Scholar
Hollenbeck, JR, Colquitt, JA, Ilgen, DR, LePine, JA and Hedlund, J (1998b) Accuracy decomposition and team decision making: Testing theoretical boundary conditions, Journal of Applied Psychology 83(3:494–500.10.1037/0021-9010.83.3.494Google Scholar
Hollenbeck, JR, Ilgen, DR, Sego, DJ, Hedlund, J, Major, DA and Phillips, J (1995) Multilevel theory of team decision making: Decision performance in teams incorporating distributed expertise, Journal of Applied Psychology 80 (2): 292–316.10.1037/0021-9010.80.2.292Google Scholar
Humphrey, SE, Hollenbeck, JR, Meyer, CJ and Ilgen, DR (2002) Hierarchical team decision making, Research in Personnel and Human Resources Management 21:175–213.10.1016/S0742-7301(02)21004-XGoogle Scholar
Ilgen, DR, Major, D, Hollenbeck, JR and Sego, D (1995) Raising an individual decision making model to the team level: A new research model and paradigm, in Guzzo, R and Salas, E (eds.) Team Effectiveness and Decision Making in Organizations, pp 113–148, Jossey-Bass, San Francisco.Google Scholar
Johnson, SD, Suriya, C, Yoon, SW, Berrett, JV and Fleur, JL (2002) Team development and group processes of virtual learning teams, Computers & Education 39(4:379–393.10.1016/S0360-1315(02)00074-XGoogle Scholar
Kang, M (2001) Team-Soar: A computational model for multilevel decision making, IEEE Transactions on Systems, Man, and Cybernetics Part A 31(6:708–714.10.1109/3468.983426Google Scholar
Kang, M (2007) The effects of agent activeness and cooperativeness on team decision efficiency: A computational simulation study using Team-Soar, International Journal of Human–Computer Studies 65(6:497–510.10.1016/j.ijhcs.2006.11.001Google Scholar
Kang, M, Waisel, LB and Wallace, WA (1998) Team-Soar: A model for team decision making, in Prietula, M, Carley, K and Gasser, L (Eds.) Simulating Organizations: Computational Models of Institutions and Groups, pp 23–45, AAAI Press / MIT Press, Menlo Park CA.Google Scholar
Klein, KJ and Kozlowski, SWJ (2000) From micro to meso: Critical steps in conceptualizing and conducting multilevel research, Organizational Research Methods 3(3:211–36.10.1177/109442810033001Google Scholar
Laird, J, Congdon, CB, Altmann, E and Doorenbos, R (1993) Soar User's Manual: Version 6. Electrical Engineering and Computer Science Department, University of Michigan, Ann Arbor MI.Google Scholar
Laird, J, Newell, A and Rosenbloom, PS (1987) SOAR: An architecture for general intelligence, Artificial Intelligence 33:1–64.10.1016/0004-3702(87)90050-6Google Scholar
LePine, JA, Hollenbeck, JR, Ilgen, DR, Colquitt, JA and Ellis, A (2002) Gender composition, situational strength, and team decision-making accuracy: A criterion decomposition approach, Organizational Behavior and Human Decision Processes 88(1:445–475.Google Scholar
LePine, JA, Hollenbeck, JR, Ilgen, DR and Hedlund, J (1997) Effects of individual differences on the performance of hierarchical decision-making teams: Much more than g, Journal of Applied Psychology 82(5:803–811.10.1037/0021-9010.82.5.803Google Scholar
Lin, Z and Carley, KM (2003) Designing stress resistant organizations: Computational theorizing and crisis applications, Kluwer, New York.10.1007/978-1-4757-3703-5Google Scholar
Massey, AP (1991) ‘Group Problem Definition: The Impact of Network Structuring Techniques on Group Effectiveness and Interaction’. Unpublished doctoral dissertation, Rensselaer Polytechnic Institute, Troy NY.Google Scholar
Miller, JG and Miller, JL (1992) Cybernetics, general systems theory, and living systems theory, in Levine, RL and Fitzgerald, HE (Eds.) Analysis of dynamic psychological systems, vol 1, pp 9–34, Plenum, New York.Google Scholar
Molleman, E (2005) The multilevel nature of team-based work research, Team Performance Management 11(3/4): 113–124.10.1108/13527590510606316Google Scholar
Moritz, SE and Watson, CB (1998) Levels of analysis issues in group psychology: Using efficacy as an example of a multilevel model, Group Dynamics 2(4:285–298.10.1037/1089-2699.2.4.285Google Scholar
O'Neil, HF Jr., Baker, EL and Kazlauskas, EJ (1992) Assessment of team performance, in Sweezy, RW and Salas, E (Eds.) Teams: Their training and performance, pp 153–175, Ablex Publishing, Norwood NJ.Google Scholar
Orasanu, J and Salas, E (1993) Team decision making in complex environments, in Klein, GAet al. (Eds.) Decision making in action: Models and methods, pp 327–345, Ablex Publishing, Norwood, NJ.Google Scholar
Phillips, JM (1999) Antecedents of leader utilization of staff input in decision-making teams, Organizational Behavior and Human Decision Processes 77(3:215–242.10.1006/obhd.1998.2819Google Scholar
Phillips, JM (2002) Antecedents and consequences of procedural justice perceptions in hierarchical decision-making teams, Small Group Research 33:32–64.Google Scholar
Prietula, MJ and Carley, KM (1994) Computational organization theory: Autonomous agents and emergent behavior, Journal of Organizational Computing 4(1:41–83.10.1080/10919399409540216Google Scholar
Sniezek, JA and Buckley, T (1995) Cueing and cognitive conflict in judge-adviser decision making, Organizational Behavior and Human Decision Processes 62:159–74.Google Scholar
Streufert, S and Nogami, G. (1992) Cognitive complexity and team decision making, in Sweezy, RW and Salas, E (eds) Teams: Their training and performance, pp 127–151, Ablex Publishing, Norwood NJ.Google Scholar