The Intertwining Impact of Intraorganizational and Routine Networks on Routine Replication Dynamics: An Agent-Based Model

Table 3

Calculating running times needed for each scenario based on power analysis.

Scenarios	Configuration of parameters (CoP)				i_NofRun	r_NofRun	EEP
Scenario I; (is_env_change? = FALSE)	Variables and values:				382	400	0.96
	K_routine	random_p		unit_AC
	1	0.1		1
	3	0.3		2
	5	0.5		3
	7	0.7
		0.9
	CoP: Φ(K_routine) ×  Φ(random_p) ×  Φ(unit_AC); = 4 × 5 × 3 = 60
Scenario II; (is_env_change? = FALSE)	Variables and values:				382	400	0.96
	K_routine	error_p		innovate_p
	1	0.1		0.2
	3	0.3		0.4
	5	0.5		0.6
	7	0.7
		0.9
	CoP:Φ(K_routine) ×  Φ(error_p) ×  Φ(innovate_p)
	= 4 × 5 × 3 = 60
Scenario III; (is_env_change? = TRUE)	Variables and values:				253	260	0.96
	K_routine	random_p	unit_AC	env_change_P
	1	0.1	1	200
	3	0.3	2	1000
	5	0.5	3
	7	0.7
		0.9
	CoP:Φ(K_routine) ×  Φ(random_p) ×  Φ(unit_AC) ×; Φ(env_change_P) = 4 × 5 × 3 × 2 = 120
Scenario IV; (is_env_change? = TRUE)	Variables and values:				253	260	0.96
	K_routine	error_p	innovate_p	env_change_P
	1	0.1	0.2	200
	3	0.3	0.4	1000
	5	0.5	0.6
	7	0.7
		0.9
	CoP:Φ(K_routine) ×  Φ(error_p) ×  Φ(innovate_p) ×  Φ(env_change_P) = 4 × 5 × 3 × 2 = 120

Notes: (1) here, the function Φ(X) represented the number of different levels involved in the variable X.