In closed systems, a direct cause-and-effect relationship exists between the initial condition and the final state of the system: When a computer's 'on' switch is pushed, the system powers up. Open systems (such as biological and social systems), however, operate quite differently. The idea of equifinality suggests that similar results may be achieved with different initial conditions and in many different ways.[1] This phenomenon has also been referred to as isotelesis[2] (from Greek ἴσος isos "equal" and τέλεσις telesis: "the intelligent direction of effort toward the achievement of an end") when in games involving superrationality.
Overview
In business, equifinality implies that firms may establish similar competitive advantages based on substantially different competencies.
In psychology, equifinality refers to how different early experiences in life (e.g., parental divorce, physical abuse, parental substance abuse) can lead to similar outcomes (e.g., childhood depression). In other words, there are many different early experiences that can lead to the same psychological disorder.
In archaeology, equifinality refers to how different historical processes may lead to a similar outcome or social formation. For example, the development of agriculture or the bow and arrow occurred independently in many different areas of the world, yet for different reasons and through different historical trajectories. This highlights that generalizations based on cross-cultural comparisons cannot be made uncritically.
In Earth and environmental Sciences, two general types of equifinality are distinguished: process equifinality (concerned with real-world open systems) and model equifinality (concerned with conceptual open systems).[3] For example, process equifinality in geomorphology indicates that similar landforms might arise as a result of quite different sets of processes. Model equifinality refers to a condition where distinct configurations of model components (e.g. distinct model parameter values) can lead to similar or equally acceptable simulations (or representations of the real-world process of interest). This similarity or equal acceptability is conditional on the objective functions and criteria of acceptability defined by the modeler. While model equifinality has various facets, model parameter and structural equifinality are mostly known and focused in modeling studies.[3] Equifinality (particularly parameter equifinality) and Monte Carlo experiments are the foundation of the GLUE method that was the first generalised method for uncertainty assessment in hydrological modeling.[4] GLUE is now widely used within and beyond environmental modeling.
See also
GLUE – Generalized Likelihood Uncertainty Estimation (when modeling environmental systems there are many different model structures and parameter sets that may be behavioural or acceptable in reproducing the behaviour of that system)[5]
TMTOWTDI – Computer programming maxim: "there is more than one way to do it"
^Jim E Freer, Keith J Beven(2001). Equifinality, data assimilation, and uncertainty estimation in mechanistic modelling of complex environmental systems using the GLUE methodology. Journal of Hydrology (2001) Volume: 249, Issue: 1–4, pp. 11–29
Publications
Bertalanffy, Ludwig von, General Systems Theory, 1968
Beven, K.J. and Binley, A.M., 1992. The future of distributed models: model calibration and uncertainty prediction, Hydrological Processes, 6, pp. 279–298.
Croft, Gary W., Glossary of Systems Theory and Practice for the Applied Behavioral Sciences, Syntropy Incorporated, Freeland, WA, Prepublication Review Copy, 1996
Durkin, James E. (ed.), Living Groups: Group Psychotherapy and General System Theory, Brunner/Mazel, New York, 1981
Mash, E. J., & Wolfe, D. A. (2005). Abnormal Child Psychology (3rd edition). Wadsworth Canada. pp. 13–14.
Weisbord, Marvin R., Productive Workplaces: Organizing and Managing for Dignity, Meaning, and Community, Jossey-Bass Publishers, San Francisco, 1987
Tang, J.Y. and Zhuang, Q. (2008). Equifinality in parameterization of process-based biogeochemistry models: A significant uncertainty source to the estimation of regional carbon dynamics, J. Geophys. Res., 113, G04010.