Equifinality

<h2 id="overview">Overview</h2>
<p>In <a href="/facts/Business/For1e8Nh">business</a>, equifinality implies that firms may establish similar competitive advantages based on substantially different competencies.
</p><p>In <a href="/facts/Psychology/duoqW7Sz">psychology</a>, equifinality refers to how different early experiences in life (e.g., parental <a href="/facts/Divorce/tENy6fK3">divorce</a>, <a href="/facts/Physical_abuse/DwMNGqpQ">physical abuse</a>, parental substance abuse) can lead to similar outcomes (e.g., <a href="/facts/Childhood_depression/sI9ut31x">childhood depression</a>). In other words, there are many different early experiences that can lead to the same <a href="/facts/Psychological_disorder/EPNjFtFf">psychological disorder</a>.
</p><p>In <a href="/facts/Archaeology/K3Q5P38R">archaeology</a>, 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.
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<h3>Model equifinality</h3>
<p>In <a href="/facts/Earth_science/rQsXCSbM">Earth</a> and <a href="/facts/Environmental_science/svr8eCse">Environmental</a> Sciences, two general types of equifinality are distinguished: <i>process equifinality</i> (concerned with real-world open systems) and <i>model equifinality</i> (concerned with conceptual open systems).<a class="footnote-ref" id="fnref:3" href="#fn:3"><sup>3</sup></a> For example, process equifinality in <a href="/facts/Geomorphology/MDf2I2h5">geomorphology</a> 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.<a class="footnote-ref" id="fnref:4" href="#fn:4"><sup>4</sup></a> Equifinality (particularly parameter equifinality) and Monte Carlo experiments are the foundation of the <a href="/facts/GLUE_(uncertainty_assessment)/29l9PLUG">GLUE method</a> that was the first generalised method for uncertainty assessment in <a href="/facts/Hydrology/Xh727cnE">hydrological modeling</a>.<a class="footnote-ref" id="fnref:5" href="#fn:5"><sup>5</sup></a> GLUE is now widely used within and beyond <a href="/facts/Natural_environment/NzGY148M">environmental</a> modeling.
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<h2 id="see-also">See also</h2>
<ul><li><a href="/facts/GLUE_(uncertainty_assessment)/29l9PLUG">GLUE – Generalized Likelihood Uncertainty Estimation</a> (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)<a class="footnote-ref" id="fnref:6" href="#fn:6"><sup>6</sup></a></li>
<li><a href="/facts/TMTOWTDI/11FCQMI1">TMTOWTDI</a> – Computer programming maxim: "there is more than one way to do it"</li>
<li><a href="/facts/Underdetermination/UyKo0zJs">Underdetermination</a></li>
<li><a href="/facts/Consilience/W2oKy2XX">Consilience</a></li>
<li><a href="/facts/Convergent_evolution/dd0L8z4R">Convergent evolution</a></li>
<li><a href="/facts/Teleonomy/5287sFD9">Teleonomy</a></li>
<li><a href="/facts/Degeneracy_(biology)/g7CkXlTP">Degeneracy (biology)</a></li>
<li><a href="/facts/Kruskal%2527s_principle/NcJAyAMg">Kruskal's principle</a></li>
<li><a href="/facts/Multicollinearity/bQXzB6sA">Multicollinearity</a></li>
<li><a href="/facts/Multiple_realizability/TkAeWXPy">Multiple realizability</a></li></ul>

<h2 id="publications">Publications</h2>
<ul><li>Bertalanffy, Ludwig von, <i>General Systems Theory</i>, 1968</li>
<li>Beven, K.J. and Binley, A.M., 1992. The future of distributed models: model calibration and uncertainty prediction, Hydrological Processes, 6, pp. 279–298.</li>
<li>Beven, K.J. and Freer, J., 2001a. <a href="https://dx.doi.org/10.1016/S0022-1694(01)00421-8">Equifinality, data assimilation, and uncertainty estimation in mechanistic modelling of complex environmental systems</a>, Journal of Hydrology, 249, 11–29.</li>
<li>Croft, Gary W., <i>Glossary of Systems Theory and Practice for the Applied Behavioral Sciences</i>, Syntropy Incorporated, Freeland, WA, Prepublication Review Copy, 1996</li>
<li>Durkin, James E. (ed.), <i>Living Groups: Group Psychotherapy and General System Theory</i>, Brunner/Mazel, New York, 1981</li>
<li>Mash, E. J., & Wolfe, D. A. (2005). <i>Abnormal Child Psychology (3rd edition)</i>. Wadsworth Canada. pp. 13–14.</li>
<li>Weisbord, Marvin R., <i>Productive Workplaces: Organizing and Managing for Dignity, Meaning, and Community</i>, Jossey-Bass Publishers, San Francisco, 1987</li>
<li>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.</li></ul>

<h2 id="references">References</h2>

<ol>
<li id="fn:1"><p>Cummings & Worley, Organization Development & Change, Thomson, 2005, p. 87. <a href="#fnref:1" class="footnote-back-ref">↩</a></p></li>
<li id="fn:2"><p>R.B. Zajonc, Feeling and Facial Efference: Implications of the Vascular Theory of Emotion. 1989, p. 16 http://psychology.stanford.edu/~lera/273/zajonc-psychreview-1989.pdf Archived 2007-06-10 at the Wayback Machine <a href="http://psychology.stanford.edu/~lera/273/zajonc-psychreview-1989.pdf" target="_blank">http://psychology.stanford.edu/~lera/273/zajonc-psychreview-1989.pdf</a> <a href="#fnref:2" class="footnote-back-ref">↩</a></p></li>
<li id="fn:3"><p>Khatami, Sina; Peel, Murray C.; Peterson, Tim J.; Western, Andrew W. (2019). "Equifinality and Flux Mapping: A New Approach to Model Evaluation and Process Representation Under Uncertainty". Water Resources Research. 55 (11): 8922–8941. Bibcode:2019WRR....55.8922K. doi:10.1029/2018WR023750. hdl:11343/286609. ISSN 1944-7973. S2CID 198397645. <a href="https://doi.org/10.1029%2F2018WR023750" target="_blank">https://doi.org/10.1029%2F2018WR023750</a> <a href="#fnref:3" class="footnote-back-ref">↩</a></p></li>
<li id="fn:4"><p>Khatami, Sina; Peel, Murray C.; Peterson, Tim J.; Western, Andrew W. (2019). "Equifinality and Flux Mapping: A New Approach to Model Evaluation and Process Representation Under Uncertainty". Water Resources Research. 55 (11): 8922–8941. Bibcode:2019WRR....55.8922K. doi:10.1029/2018WR023750. hdl:11343/286609. ISSN 1944-7973. S2CID 198397645. <a href="https://doi.org/10.1029%2F2018WR023750" target="_blank">https://doi.org/10.1029%2F2018WR023750</a> <a href="#fnref:4" class="footnote-back-ref">↩</a></p></li>
<li id="fn:5"><p>Beven, Keith; Binley, Andrew (1992). "The future of distributed models: Model calibration and uncertainty prediction". Hydrological Processes. 6 (3): 279–298. Bibcode:1992HyPr....6..279B. doi:10.1002/hyp.3360060305. ISSN 1099-1085. <a href="https://onlinelibrary.wiley.com/doi/abs/10.1002/hyp.3360060305" target="_blank">https://onlinelibrary.wiley.com/doi/abs/10.1002/hyp.3360060305</a> <a href="#fnref:5" class="footnote-back-ref">↩</a></p></li>
<li id="fn:6"><p>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 <a href="#fnref:6" class="footnote-back-ref">↩</a></p></li>
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Equifinality open-in-new

Equifinality