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Looking backwards

The entire management enterprise has been built on efforts directed towards efficiency (with varying emphases over the decades; Scott, 2003). This can be defined as the appropriate disposal of resources such that either the least possible inputs are used to produce an output or more output comes from the exploitation of a given amount of inputs (e.g., Simon, 1997). This approach has provided a tremendous support to the development of management as a discipline and it still contributes to the way management is practiced. As a result of this, we know a great deal about how to structure, plan, create, organize, maintain and improve processes, procedures, and routines (Abrahamson, 2002). But we know very little when it comes to de-organize, create simpler from complex structures, isolate and debunk unnecessary routines, reduce bureaucracy to functional levels, for example (Abrahamson & Freeman, 2007). Some have categorized all these aspects under the umbrella of disorganization management (Herath et al., 2015, 2017).

Looking forward

However, today's organizations are sometimes required to move toward more flexible and adaptive forms (Fioretti, 2012) due to an ever changing environment and workforce. A combination of flexibility and adaptability that makes internal organizational processes malleable and open to change is summarized here with plasticity, for lack of a better word. One of the challenges of this area of study is that it is both costly and difficult to study. It is so because it usually is practiced by trial-and-error in a fluid process that makes decisions happen while they are made (so called through doing Magnani, 2007; Secchi, 2011). This makes advanced computational simulation techniques particularly useful. On the one hand, they allow for a representation of a complex adaptive system (Miller & Page, 2007). On the other hand, they (can) maintain strong ties with actual organizations, making their findings particularly relevant.

Key topics

The idea of this symposium starts from these grounds to propose an agent-based computational simulation (ABM) approach to the study of the plastic organization. The symposium welcomes contributions from any discipline, including but not limited to psychology, sociology, management, computer science, engineering, cognitive science, decision science, language, artificial intelligence, economics, philosophy. Submissions may range from empirical investigations, to cross-methods studies, and to theoretical and philosophical perspectives.

This Call for Abstracts is to encourage proposals that address but are not limited to the following:

• What is the plastic organization? What are its characteristics and possible shapes? What make it such?
• What are the characteristics of the individuals that deal with plasticity within the organization? How could contemporary cognitive paradigms such as distributed (Hutchins, 1995) or systemic cognition (Cowley & Vallee-Tourangeau, 2013) help us understand cognitive mechanisms that support or hinder change?
• How is organizational cognition framed in a plastic organization? How is it different from a standard/non-adaptive organization? Recent work on the crisis of standard cognitive paradigms (Secchi & Adamsen, 2017; Secchi & Cowley, 2016) might be of help.
• What is the limit of organizational flexibility? How much and what kind of flexibility leads to better (or worse) decision making outcomes? Micro and macro levels of analyses are both considered and relevant here.
• Through the famous `garbage can' model (Cohen et al., 1972), the literature indicated that anarchy is sometimes preferable to hierarchy (Fioretti & Lomi, 2010; Herath et al., 2015). Are there other alternatives to the anarchy-hierarchy model? How so?

References

Abrahamson, E. (2002). Disorganization theory and disorganizational behavior. Research in Organizational Behavior, 24, 139-180.

Abrahamson, E. & Freeman, D. H. (2007). A Perfect Mess: The Hidden Benefits of Disorder. New York: Little Brown.

Cohen, M. D., March, J. G., & Olsen, H. P. (1972). A garbage can model of organizational choice. Administrative Science Quarterly, 17 (1), 1-25.

Cowley, S. J. & Vallee-Tourangeau, F. (Eds.). (2013). Cognition beyond the brain. Computation, interactivity and human artifice. London: Springer.

Fioretti, G. (2012). Two measures of organizational flexibility. Journal of Evolutionary Economics, 22 (5), 957-979.

Fioretti, G. & Lomi, A. (2010). Passing the buck in the garbage can model of organizational choice. Computational and Mathematical Organization Theory, 16 (2), 113-143.

Herath, D., Costello, J., & Homberg, F. (2017). Team problem solving and motivation under disorganization – an agent-based modeling approach. Team Performance Management, 23 (1/2), 46-65.

Herath, D., Secchi, D., & Homberg, F. (2015). Simulating the effects of disorganisation on employee goal setting and task performance. In D. Secchi & M. Neumann (Eds.), Agent-Based Simulation of Organizational Behavior. New Frontiers of Social Science Research (pp. 63-84). New York: Springer.

Hutchins, E. (1995). Cognition in the wild. Cambridge, MA: MIT Press.

Magnani, L. (2007). Morality in a technological world. Knowledge as a duty. New York: Cambridge University Press.

Miller, J. H. & Page, S. E. (2007). Complex Adaptive Systems. An Introduction to Computational Models of Social Life. Princeton, NJ: Princeton University Press.

Scott, W. R. (2003). Organizations. Rational, Natural, and Open Systems (5th edition ed.). Englewood Cli s, NJ: Prentice-Hall.

Secchi, D. (2011). Extendable rationality. Understanding decision making in organizations. New York: Springer.

Secchi, D. (2017). Guest editorial: Agent-based models of bounded rationality. Team Performance Management, 23 (1/2), 2-12.

Secchi, D. & Adamsen, B. (2017). Organizational cognition: A critical perspective on the theory in use. In S. J. Cowley & F. Vallee-Tourangeau (Eds.), Cognition Beyond the Brain: Computation, Interactivity and Human Artifice (2nd ed.). (pp. 305-331). Heidelberg: Springer.

Secchi, D. & Cowley, S. J. (2016). Organisational cognition: What it is and how it works. In European Academy of Management Annual Conference. Paris, France.

Secchi, D. & Neumann, M. (Eds.). (2016). Agent-Based Simulation of Organizational Behavior. New Frontiers of Social Science Research. New York: Springer.

Simon, H. A. (1997). Administrative behavior (4th ed.). New York: The Free Press.