Abstract
The idea that individuals do not make decisions in isolation is not new in the behavioral sciences. In fact, it was one of the founding fathers of the discipline, Herbert A. Simon, who suggested individuals depend on opinions, recommendations, information, and advice coming from other human beings and labeled it “docility.” Limited attention has been devoted to the study of this key characteristic of decision makers. This chapter takes the original model of docility, expands it, and applies it to individuals in structured or formal social systems (e.g., organizations). This exercise is performed using agent-based modeling and it explores under what circumstances organizational “docility” is supported or not.
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Notes
- 1.
The modified fitness equations are:
$$\displaystyle\begin{array}{rcl} fI& =& fn + fd \cdot dI + faI \cdot qI \cdot cI + faU \cdot qU \cdot cU - c \cdot cI {}\end{array}$$(9.1)$$\displaystyle\begin{array}{rcl} fS& =& fn + faI \cdot qI \cdot cI + faU \cdot qU \cdot cU {}\end{array}$$(9.2)$$\displaystyle\begin{array}{rcl} fU& =& fn + fd \cdot dU + faI \cdot qI \cdot cI + faU \cdot qU \cdot cU - c \cdot cU {}\end{array}$$(9.3)where fI, fS, and fU are the net fitness of intelligent altruist, selfish, and unintelligent altruist individuals, respectively. The other symbols in the equations are: fn that is the natural fitness, common to everyone in the system; fd ⋅ dI and fd ⋅ dU are incremental fitness due to docility, multiplied by the coefficient for intelligent and unintelligent altruists; faI and faU are fitness gains from other altruists; […] cI and cU are the extent to which I and U behave altruistically; c is the cost of altruism (Simon, 1993, pp. 157–158). In our ABM, qI and qU represent how many other intelligent and unintelligent docile individuals are in the specified range.
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Appendix
Appendix
The following statistical tests were performed to circumstantiate results where the figures do not seem to provide a clear definite indication of what is happening.
1.1 Impact = −0. 1
A t-test confirms that ud numbers are different when cost is at 0. 05—\(t = 33.38,df = 160.47,p <0.001\)—for ud range = 9 and ud range = 12. Another test shows similar results when cost is lowered to 0. 005: \(t = 32.95,df = 177.11,p <0.001\).
The distribution of nd in the case of range = 12 and cost = 0. 05 is significantly different from ud—\(t = 45.40,df = 182.67,p <0.001\)—and from id—\(t = -13.94,df = 139.36,p <0.001\)—with mean nd = 42. 14, mean id = 28. 89, and mean ud = 108. 96. When range=12 and cost=0.005 nd are also significantly different from ud—\(t = 49.04,df = 177.13,p <0.001\)—and from id—\(t = -16.25,df = 152.71,p <0.001\)—with mean nd = 41. 85, mean id = 27. 15, and mean ud = 110. 99.
1.2 Impact = 0. 1
A battery of t-tests show that results are significantly different when range = 3 and cost is either 0. 05 or 0. 005. In the former case, we have \(t = -8.06,df = 136.19,p <0.001\), with mean ud = 53. 42 and mean nd = 57. 12. In the latter case, the test is \(t = -9.11,df = 139.85,p <0.001\), with mean ud = 52. 46 and mean nd = 57. 30. This also implies that there is no significant difference in ud numbers under these conditions—\(t = -0.65,df = 193.18,p = 0.52\). Some additional tests also show that there is no significant difference between nd and ud when range = 6 and cost = 0. 05: \(t = -1.33,df = 199.81,p = 0.18\), with mean ud = 33. 27 and mean nd = 35. 73. These two types follow a very similar pattern when range = 6 and cost = 0. 05: \(t = -1.33,df = 199.81,p = 0.18\).
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Secchi, D. (2016). Boundary Conditions for the Emergence of “Docility” in Organizations: Agent-Based Model and Simulation. In: Secchi, D., Neumann, M. (eds) Agent-Based Simulation of Organizational Behavior. Springer, Cham. https://doi.org/10.1007/978-3-319-18153-0_9
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