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Developing a computational model to understand the contributions of social learning modes to task coordination in teams

Published online by Cambridge University Press:  15 January 2013

Vishal Singh ,
Andy Dong  and
John S. Gero
Vishal Singh*
Affiliation:
Department of Civil and Structural Engineering, Aalto University, Espoo, Finland
Andy Dong
Affiliation:
Faculty of Engineering and Information Technology, University of Sydney, Sydney, Australia
John S. Gero
Affiliation:
Krasnow Institute of Advanced Study, George Mason University, Fairfax, Virginia, USA
*
Reprint requests to: Vishal Singh, Department of Civil and Structural Engineering, Aalto University, Espoo 0076, Finland. E-mail: [email protected]
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Abstract

This paper reports on a computational model developed to study the effects of various modes of social learning on task coordination in teams through the mapping of distributed team competence, a significant aspect of efficient teamwork. The computational model emphasizes and operationalizes distinct modes of social learning, differentiated in terms of socialization opportunities. Simulation results demonstrate that computational models based on fundamental principles of social learning provide a robust approach to study task coordination in teams and can be used to explore ways to organize opportunities for social learning depending upon member retention, team structure, and the complexity of the design task.

Keywords

Member RetentionSocial LearningTeam StructureTransactive Memory
Type
Regular Articles
Information
AI EDAM , Volume 27 , Issue 1 , February 2013 , pp. 3 - 17
Copyright
Copyright © Cambridge University Press 2013

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References

REFERENCES

Argote, L. (1999). Organizational Learning: Creating, Retaining, and Transferring Knowledge. New York: Kluwer Academic.Google Scholar
Axelrod, R. (1997). Advancing the art of simulation in the social sciences. In Simulating Social Phenomena (Conte, R., Hegselmann, R., & Terna, P., Eds.), pp. 21–40. Berlin: Springer.CrossRefGoogle Scholar
Badke-Schaub, P., Neumann, A., Lauche, K., & Mohammed, S. (2007). Mental models in design teams: A valid approach to performance in design collaboration? CoDesign 3, 5–20.CrossRefGoogle Scholar
Bellifemine, F., Caire, G., & Greenwood, D. (2007). Developing Multi-Agent Systems With JADE. Sussex: Wiley.CrossRefGoogle Scholar
Bobrow, D.G., & Whalen, J. (2002). Community knowledge sharing in practice: the Eureka story. Reflections 4, 47–59.CrossRefGoogle Scholar
Borgatti, S.P., & Cross, R. (2003). A relational view of information seeking and learning in social networks. Management Science 49, 432–445.CrossRefGoogle Scholar
Brown, D.C. (1996). Routineness revisited. In Mechanical Design: Theory and Methodology (Waldron, M., & Waldron, K., Eds.), pp. 195–208. New York: Springer–Verlag.CrossRefGoogle Scholar
Carley, K. (1992). Organizational learning and personnel turnover. Organization Science 3, 20–46.CrossRefGoogle Scholar
Carley, K.M., & Svoboda, D.M. (1996). Modeling organizational adaptation as a simulated annealing process. Sociological Methods Research 25, 138–168.CrossRefGoogle Scholar
Clancy, T. (1994). The latest word from thoughtful executives—the virtual corporation, telecommuting and the concept of team. Academy of Management Executive 8(2), 8–10.Google Scholar
Conlon, T.J. (2004). A review of informal learning literature, theory and implications of practice in developing global professional competence. Journal of European Industrial Training 28, 283–295.CrossRefGoogle Scholar
Desanctis, G., & Monge, P. (1999). Introduction to the special issue: communication processes for virtual organizations. Organization Science 10, 693–703.CrossRefGoogle Scholar
Entin, E.E., & Sarfaty, D. (1999). Adaptive team coordination. Human Factors 41, 312–325.CrossRefGoogle Scholar
Eppinger, S., & Salminen, V. (2001). Patterns of product development interactions. Proc. Int. Conf. Engineering Design, pp. 283–290. Glasgow: Design Science.Google Scholar
Espinosa, J.A., Kraut, R.E., Slaughter, S.A., Lerch, J.F., Herbsleb, J.D., & Mockus, A. (2002). Shared mental models, familiarity and coordination: A multi-method study of distributed software teams. Proc. Int. Conf. Information Systems, ICIS 2002, Barcelona.Google Scholar
FIPA. (2002). Foundation for intelligent physical agents, FIPA ACL Message Structure Specification. Accessed at http://www.fipa.org/specs/fipa00061/SC00061G.pdf on March 6, 2006.Google Scholar
Gero, J.S. (1990). Design prototypes: a knowledge representation schema for design, AI Magazine 11(4), 26–36.Google Scholar
Gilbert, D.T., & Osborne, R.E. (1989). Thinking backward some curable and incurable consequences of cognitive busyness. Journal of Personality and Social Psychology 57, 940–949.CrossRefGoogle Scholar
Gilbert, D.T., Pelham, B.W., & Krull, D.S. (1988). On cognitive busyness, when person perceivers meet persons perceived. Journal of Personality and Social Psychology 54, 733–740.CrossRefGoogle Scholar
Grant, R.M. (1996). Toward a knowledge-based theory of the firm. Strategic Management Journal 17, 109–122.CrossRefGoogle Scholar
Grecu, D.L., & Brown, D.C. (1998). Dimensions of machine learning in design. Artificial Intelligence for Engineering Design, Analysis and Manufacturing 12(2), 117–121.CrossRefGoogle Scholar
Hackman, J.R. (1987). The design of work teams. In Handbook of Organizational Behavior (Lorsch, J., Ed.). Englewood Cliffs, NJ: Prentice–Hall.Google Scholar
Harrison, D.A., Mohammed, S., McGrath, J.E., Florey, A.T., & Vanderstoep, S.W. (2003). Time matters in team performance: effects of member familiarity, entertainment, and task discontinuity on speed and quality. Personnel Psychology 56, 633–669.CrossRefGoogle Scholar
Hinds, P.J., Carley, K.M., Krackhardt, D., & Wholey, D. (2000). Choosing work group members: balancing similarity, competence, and familiarity. Organizational Behavior and Human Decision Processes 81, 226–251.CrossRefGoogle ScholarPubMed
Huber, G.P. (1981). The nature of organizational decision making and the design of decision support systems. MIS Quarterly 5, 1–10.CrossRefGoogle Scholar
Huckman, R.S., & Staats, B.R. (2008). Variation in experience and team familiarity: addressing the knowledge acquisition–application problem. Harvard Business School Weekly. Accessed at http://hbswk.hbs.edu/item/6034.htmlGoogle Scholar
Huckman, R.S., Staats, B.R., & Upton, D.M. (2008). Team familiarity, role experience, and performance: evidence from Indian software services. Harvard Business School Weekly. Accessed at http://hbswk.hbs.edu/item/5785.htmlGoogle Scholar
Irene Frieze, B.W. (1971). Cue utilization and attributional judgments for success and failure. Journal of Personality 39, 591–605.CrossRefGoogle Scholar
Jin, Y., Levitt, R.E., Christiansen, T.R., & Kunz, J.C. (1995). The virtual design team: modeling organizational behavior of concurrent design teams. Artificial Intelligence for Engineering Design, Analysis and Manufacturing 9, 145–158.CrossRefGoogle Scholar
Katzenbach, S.D. Jr. (1993). The discipline of teams. Harvard Business Review 71, 111–120.Google ScholarPubMed
Knobe, J., & Malle, B.F. (2002). Self and other in the explanation of behavior: 30 years later. Psychological Belgica 42, 113–130.CrossRefGoogle Scholar
Kunz, J.C., Levitt, R.E., & Jin, Y. (1998). The virtual design team: a computational simulation model of project organizations. Communications of the Association for Computing Machinery 41, 84–92.CrossRefGoogle Scholar
Langan-Fox, J., Anglim, J., & Wilson, J.R. (2004). Mental models, team mental models, and performance: process, development, and future directions. Human Factors in Ergonomics and Manufacturing 14, 331–352.CrossRefGoogle Scholar
Leinonen, P., Jarvela, S., & Hakkinen, P. (2005). Conceptualizing the awareness of collaboration: a qualitative study of a global virtual team. Computer Supported Cooperative Work 14, 301–322.CrossRefGoogle Scholar
Malle, B.F. (2005). Folk theory of mind: Conceptual foundations of human social cognition. In The New Unconscious (Hassin, R., Uleman, J.S., & Bargh, J.A., Eds.). New York: Oxford University Press.Google Scholar
Malone, T.W. (1987). Modeling coordination in organizations and markets. Management Science 33, 1317–1332.CrossRefGoogle Scholar
Marsick, V., & Watkins, K. (1997). Lessons from informal and incidental learning. In Management Learning: Integrating Perspectives in Theory and Practice (Burgoyne, J., & Reynolds, M., Eds.), pp. 295–311. Thousand Oaks, CA: Sage.CrossRefGoogle Scholar
Mathieu, J.E., Heffner, T.S., Goodwin, G.F., Salas, E., & Cannon-Bowers, J.A. (2000). The influence of shared mental models on team process and performance. Journal of Applied Psychology 85, 273–283.CrossRefGoogle Scholar
McDonough, E.F., Kahn, K.B., & Barczak, G. (2001). An investigation of the use of global, virtual, and colocated new product development teams. Journal of Product Innovation Management 18, 110–120.CrossRefGoogle Scholar
McGrew, W.C. (1998). Culture in nonhuman primates? Annual Review of Anthropology 27, 301–328.CrossRefGoogle Scholar
Mohammed, S., Klimoski, R., & Rentsch, J. (2000). The measurement of team mental models: We have no shared schema. Organizational Research Methods 3, 123–165.CrossRefGoogle Scholar
Monge, P., & Contractor, N. (2003). Theories of Communication Networks. New York: Oxford University Press.CrossRefGoogle Scholar
Moreland, R.L. (1999). Transactive memory: learning who knows what in work group and organizations. In Shared Cognition in Organization: The Management of Knowledge (Thompson, L.L., Levine, J.M., & Messick, D.M., Eds.), pp. 3–31. Mahwah, NJ: Erlbaum.CrossRefGoogle Scholar
Moreland, R.L., Agote, L., & Krishnan, R. (1998). Training people to work in groups. Theory and Research on Small Groups (Tindale, R.S., & Heanth, L., Eds.), Vol. 4, pp. 37–60. New York: Plenum.CrossRefGoogle Scholar
OpenLearn. (2009). Types of Teams. Accessed at http://openlearn.open.ac.uk/mod/resource/view.php?id=09209 on March 24, 2009.Google Scholar
Perkins, S. (2005). Building and managing a successful design team. STEPMagazine. Accessed at http://www.stepinsidedesign.com/STEPMagazine/Article/28410/0/page/1Google Scholar
Rao, D.R., & Argote, L. (2006). Organizational learning and forgetting: The effects of turnover and structure. European Management Review 3, 77–85.CrossRefGoogle Scholar
Ravenscroft, I. (2004). Folk Psychology as a Theory. Accessed at http://plato.stanford.edu/archives/fall2008/entries/folkpsych-theory on March 24, 2009.Google Scholar
Reagans, R., Argote, L., & Brooks, D. (2005). Individual experience and experience working together: Predicting learning rates from knowing who knows what and knowing how to work together. Management Science 51, 869–881.CrossRefGoogle Scholar
Ren, Y., Carley, K.M., & Argote, L. (2001). Simulating the Role of Transactive Memory in Group Training and Performance. Pittsburgh, PA: Carnegie Melon University, CASOS, Department of Social and Decision Sciences.Google Scholar
Ren, Y., Carley, K.M., & Argote, L. (2006). The contingent effects of transactive memory: when is it more beneficial to know what others know? Management Science 52, 671–682.CrossRefGoogle Scholar
Rodan, S. (2008). Organizational learning: Effects of (network) structure and (individual) strategy. Computational & Mathematical Organization Theory 14, 222–247.CrossRefGoogle Scholar
Rouse, W., Cannon-Bowers, J., & Salas, E. (1992). The role of mental models in team performance in complex systems. IEEE Transactions on Systems, Man, and Cybernetics 22, 1296–1308.CrossRefGoogle Scholar
Seshasai, S., Malter, A.J., & Gupta, A. (2006). The use of information systems in collocated and distributed teams: a test of the 24-hour knowledge factory (Eller College of Management Working Paper No. 1034-06). Accessed at http://ssrn.com/abstract=935106Google Scholar
Siddique, Z., & Rosen, D.W. (2001). On combinatorial design spaces for the configuration design of product families. Artificial Intelligence for Engineering Design, Analysis and Manufacturing 15, 91–108.CrossRefGoogle Scholar
Simon, H.A. (1991). Bounded rationality and organizational learning. Organization Science 2, 125–134.CrossRefGoogle Scholar
Singh, V. (2010). Computational studies on the role of social learning in the formation of team mental models. PhD Thesis, University of Sydney, Department of Architecture, Design and Planning.Google Scholar
Skeels, M.M., & Grudin, J. (2009). When social networks cross boundaries: A case study of workplace use of Facebook and Linked. Proc. ACM 2009 Int. Conf. Supporting Group Work, GROUPS'09, pp. 95–103. New York: ACM.CrossRefGoogle Scholar
Sosa, M.E., Eppinger, S.D., & Rowles, C.M. (2004). The misalignment of product architecture and organizational structure in complex product development. Management Science 50, 1674–1689.CrossRefGoogle Scholar
Staats, B.R. (2011). Unpacking team familiarity: The effect of geographic location and hierarchical role. Production and Operations Management. Advance online publication. doi:10.1111/j.1937-5956.2011.01254.xGoogle Scholar
Sutherland, J., Viktorov, A., Blount, J., & Puntikov, N. (2007). Distributed scrum: agile project management with outsourced development teams. Proc. HICSS'40, Hawaii Int. Conf. Software Systems.CrossRefGoogle Scholar
Tomasello, M. (1999). The Cultural Origins of Human Cognition. Cambridge, MA: Harvard University Press.Google Scholar
Townley, B., Beech, N., & Mckinlay, A. (2009). Managing in the creative industries: managing the motley crew. Human Relations 62, 939–962.CrossRefGoogle Scholar
Wallace, D.M., & Hinsz, V.B. (2009). Group members as actors and observers in attributions of responsibility for group performance. Small Group Research 40, 52–71.CrossRefGoogle Scholar
Wegner, D. (1987). Transactive memory: A contemporary analysis of the group mind. In Theories of Group Behavior (Mullen, B., & Goethals, G.R., Eds.), pp. 185–208. New York: Springer–Verlag.CrossRefGoogle Scholar
Wijngaards, N.J.E., Boonstra, H.M., & Brazier, F.M.T. (2004). The role of trust in distributed design. Artificial Intelligence for Engineering Design, Analysis and Manufacturing 18, 199–209.CrossRefGoogle Scholar
Wu, Z., & Duffy, A.H.B. (2004). Modeling collective learning in design. Artificial Intelligence for Engineering Design, Analysis and Manufacturing 18, 289–313.CrossRefGoogle Scholar