Hostname: page-component-758b78586c-9l7gn Total loading time: 0 Render date: 2023-11-27T20:23:53.002Z Has data issue: false Feature Flags: { "corePageComponentGetUserInfoFromSharedSession": true, "coreDisableEcommerce": false, "useRatesEcommerce": true } hasContentIssue false

How do analogizing and mental simulation influence team dynamics in innovative product design?

Published online by Cambridge University Press:  27 April 2015

Hernan Casakin*
School of Architecture, Ariel University, Ariel, Israel
Linden J. Ball
School of Psychology, University of Central Lancashire, Preston, United Kingdom
Bo T. Christensen
Department of Marketing, Copenhagen Business School, Copenhagen, Denmark
Petra Badke-Schaub
Faculty of Industrial Design Engineering, Delft University of Technology, Delft, the Netherlands
Reprint requests to: Hernan Casakin, School of Architecture, Ariel University, P.O. Box 3, 44837, Ariel, Israel. E-mail:


The aim of this study was to gain further insight into how analogical reasoning and mental simulation, two cognitive strategies, influence team dynamics in innovative product design. A particular emphasis was placed on exploring the association between these two strategies and team cohesion and team collaboration. Analogies were coded for “analogical distance” (i.e., within domain or between domain) and “analogical purpose” (i.e., problem identification, function finding, solution generation, and explanation). The results indicated that the presence of either analogizing or mental simulation was related to team cohesion and team collaboration, with mental simulation having an especially marked association with team collaboration. Within-domain analogizing was found to enhance team collaboration, but it did not influence team cohesion. Furthermore, all types of analogical purpose showed a similar association with team cohesion, whereas solution generation and function finding had a stronger association with team collaboration. We propose that analogizing and mental simulations are strategies that serve valuable functions in engendering enhanced cohesion and collaboration, which might be expected to lead to more effective design outcomes, although this remains an empirical question in need of further corroboration.

Special Issue Articles
Copyright © Cambridge University Press 2015 

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.)



Badke-Schaub, P., Neumann, A., & Lauche, K. (2011). An observation-based method for measuring the sharedness of mental models in teams. In Coordination in Human and Primate Groups (Boos, M., Kolbe, M., Kappeler, P.M., & Ellwart, T., Eds.), pp. 177197. Berlin: Springer–Verlag.Google 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 (1), 520.Google Scholar
Ball, L.J., & Christensen, B.T. (2009). Analogical reasoning and mental simulation in design: two strategies linked to uncertainty resolution. Design Studies 30 (2), 567589.Google Scholar
Ball, L.J., Lambell, N.J., Ormerod, T.C., Slavin, S., & Mariani, J.A. (2001). Representing design rationale to support innovative design re-use: a minimalist approach. Journal of Automation in Construction 10 (6), 663674.Google Scholar
Ball, L.J., Onarheim, B., & Christensen, B.T. (2010). Design requirements, epistemic uncertainty and solution development strategies in software design. Design Studies 31 (6), 567589.Google Scholar
Ball, L.J., Ormerod, T.C., & Morley, N.J. (2004). Spontaneous analogising in engineering design: a comparative analysis of experts and novices. Design Studies 25 (5), 495508.Google Scholar
Beal, D.J., Cohen, R.R., Burke, M.J., & McLendon, C.L. (2003). Cohesion and performance in groups: a meta-analytic clarification of construct relations. Journal of Applied Psychology 88 (6), 9891004.Google Scholar
Bearman, C.R., Ball, L.J., & Ormerod, T.C. (2007). The structure and function of spontaneous analogising in domain-based problem solving. Thinking & Reasoning 13 (3), 273294.Google Scholar
Bollen, K.A., & Hoyle, R.H. (1990). Perceived cohesion: a conceptual and empirical examination. Social Forces 69 (2), 479504.Google Scholar
Carron, A.V., & Brawley, L.R. (2000). Cohesion: conceptual and measurement issues. Small Group Research 31 (1), 89106.Google Scholar
Casakin, H. (2004). Visual analogy as a cognitive strategy in the design process: expert versus novice performance. Journal of Design Research 4 (2).Google Scholar
Casakin, H. (2010). Visual analogy, visual displays, and the nature of design problems: the effect of expertise. Environment and Planning B: Planning and Design 37 (1), 170188.Google Scholar
Casakin, H. (2012). Visual analogy as a cognitive stimulator for idea generation in design problem solving. In The Psychology of Problem Solving: An Interdisciplinary Approach (Helie, S., Ed.), New York: Nova Science.Google Scholar
Casakin, H., & Badke-Schaub, P. (2013). The psychology of creativity: mental models in design teams. In Psychology of Creativity (Antonietti, A., Colombo, B., & Memmert, D., Eds.), pp. 167180. New York: Nova Science.Google Scholar
Casakin, H., & Goldschmidt, G., (1999). Expertise and the visual use of analogy: implications for design education. Design Studies 20 (2), 153175.Google Scholar
Casakin, H., & Goldschmidt, G. (2000). Reasoning by visual analogy in design problem-solving: the role of guidance. Environment and Planning B: Planning and Design 27 (1), 105119.Google Scholar
Christensen, B.T., & Schunn, C.D. (2007). The relationship of analogical distance to analogical function and pre-inventive structure: the case of engineering design. Memory & Cognition 35 (1), 2938.Google Scholar
Christensen, B.T., & Schunn, C.D. (2009). The role and impact of mental simulation in design. Applied Cognitive Psychology 23 (3), 327344.Google Scholar
Clement, J.J. (2008). Creative Model Construction in Scientists and Students: The Role of Imagery, Analogy, and Mental Simulation. Dordrecht: Springer.Google Scholar
Coskun, H., Paulus, P.B., Brown, V., & Sherwood, J.J. (2000). Cognitive stimulation and problem presentation in idea-generating groups. Group Dynamics: Theory, Research, & Practice 4 (4), 307329.Google Scholar
Dahl, D., & Wand Moreau, P. (2002). The influence and value of analogical thinking during new product ideation. Journal of Marketing Research 39 (1), 760.Google Scholar
Den Otter, A., & Emmitt, S. (2008). Design team communication and design task complexity: the preference for dialogues. Architectural Engineering and Design Management 4 (2), 121129.Google Scholar
Dunbar, K., & Blanchette, I. (2001). The in vivo/in vitro approach to cognition: the case of analogy. Trends in Cognitive Sciences 5 (8), 334339.Google Scholar
Forsyth, D.R. (2010). Group Dynamics, 5th ed.Wadsworth: Cengage Learning.Google Scholar
Fu, K., Cagan, J., & Kotovsky, K. (2010). Design team convergence: the influence of example solution quality. Journal of Mechanical Design 132 (11), 111005/1111005/11.Google Scholar
Gardner, R. (1997). The conversation object mm: a weak and variable acknowledging token. Research on Language & Social Interaction 30 (2), 131156.Google Scholar
Gentner, D. (2002). Psychology of mental models. In International Encyclopedia of the Social and Behavioral Sciences (Smelser, N.J., & Bates, P.B., Eds.), pp. 96839687. Amsterdam: Elsevier.Google Scholar
Goel, A.K., & Wiltgen, B. (2014). On the role of analogy in resolving cognitive dissonance in collaborative interdisciplinary design. In Case-Based Reasoning Research and Development (Lamontagne, L., & Plaza, E., Eds.), LNCS, Vol. 8765, pp. 185199. Berlin: Springer–Verlag.Google Scholar
Goldschmidt, G. (1995). Visual displays for design: imagery, analogy and databases of visual images. In Visual Databases in Architecture (Koutamanis, A., Timmermans, H., & Vermeulen, I., Eds.), pp. 5374. Aldershot: Avebury.Google Scholar
Helms, M., Vattam, S.S., & Goel, A.K. (2009). Biologically inspired design: process and products. Design Studies 30 (5), 606622.Google Scholar
Helms, M., Vattam, S.S., & Goel, A.K. (2010). The effect of functional modeling on understanding complex biological systems. Proc. ASME 2010 Int. Design Engineering Technical Conf. and Computers & Information in Engineering Conf., pp. 107–115, Montreal, August 15–18, 2010.Google Scholar
Holyoak, K.J., & Thagard, P. (1995). Mental Leaps: Analogy in Creative Thought. Cambridge, MA: MIT Press.Google Scholar
Johnson-Laird, P.N. (1983). Mental Models: Towards a Cognitive Science of Language, Inference, and Consciousness. Cambridge: Cambridge University Press.Google Scholar
Kleinsmann, M.S., & Valkenburg, R. (2007). Why do(n't) actors in collaborative design understand each other? An empirical study towards a better understanding of collaborative design. CoDesign 3 (1), 5973.Google Scholar
Kohn, N.W., Paulus, P.B., & Choi, Y. (2011). Building on ideas of others: an examination of the idea combination process. Journal of Experimental Social Psychology 47 (3), 544561.Google Scholar
Linsey, J.S., Clauss, E.F., Kurtoglu, T., Murphy, J.T., Wood, K.L., & Markman, A.B. (2011). An experimental study of group idea generation techniques: understanding the roles of idea representation and viewing methods. Journal of Mechanical Design 133 (3), 031008/1031008/15.Google Scholar
McDonnell, J., & Lloyd, P. (2009). About: Designing—Analysing Design Meetings. London: Taylor & Francis.Google Scholar
Nersessian, N.J. (2008). Creating Scientific Concepts. Cambridge, MA: MIT Press.Google Scholar
Ormerod, T.C., Mariani, J.A., Ball, L.J., & Lambell, N.J. (1999). Desperado: three-in-one indexing for innovative design. Proc. 7th IFIP Conf. Human-Computer Interaction—INTERACT ’99 (Sasse, M.A., & Johnson, C., Eds.), pp. 336–343. London: IOS Press.Google Scholar
Owen, W.F. (1985). Metaphor analysis of cohesiveness in small discussion groups. Small Group Research 16 (3), 415424.Google Scholar
Richardson, M., & Ball, L.J. (2009). Internal representations, external representations and ergonomics: towards a theoretical integration. Theoretical Issues in Ergonomics Science 10 (4), 335376.Google Scholar
Sannomiya, M., Kawaguchi, A., Yamakawa, I., & Morita, Y. (2003). Effect of backchannel utterances on facilitating idea-generation in Japanese think-aloud tasks. Psychological Reports 93 (1), 4146.Google Scholar
Stempfle, J., & Badke-Schaub, P. (2002). Thinking in design teams: an analysis of team communication. Design Studies 23 (5), 473496.Google Scholar
Trickett, S.B., & Trafton, J.G. (2002). The instantiation and use of conceptual simulations in evaluating hypotheses: movies-in-the-mind in scientific reasoning. Proc. 24th Annual Conf. Cognitive Science Society, pp. 878–883. Mahwah, NJ: Erlbaum.Google Scholar
Tseng, I., Moss, J., Cagan, J., & Kotovsky, K. (2008). The role of timing and analogical similarity in the stimulation of idea generation in design. Design Studies 29 (3), 203221.Google Scholar
Vattam, S.S., Helms, M.E., & Goel, A.K. (2010). A content account of creative analogies in biologically inspired design. Artificial Intelligence for Engineering Design, Analysis and Manufacturing 24 (4), 467481.Google Scholar
Wiltschnig, S., Christensen, B.T., & Ball, L.J. (2013). Collaborative problem-solution co-evolution in creative design. Design Studies 34 (5), 515542.Google Scholar
Wolf, J.P. (2008). The effects of backchannels on fluency in L2 oral task production. System 36 (2), 279294.Google Scholar
Young, R.F., & Lee, J. (2004). Identifying units in interaction: reactive tokens in Korean and English conversations. Journal of Sociolinguistics 8 (3), 380407.Google Scholar