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

Table 1

Definition of agent attributes.

Attributes	Definition
unitID	A unique ID number for agent identification.
unitNeighbors	Every unit agent owned a list of neighbors defined by the intraorganizational network structure. Here, we assumed a classic random network following Erdös and Rényi [74], where nodes represented unit agents and linkages between nodes – which represented their neighborhoods – were randomly assigned by the probability value random_p (0 ≤ random_p ≤ 1). Given the bounded rationality characterizing organizational actors [75], we assumed that each unit agent could only interact with and replicate routines from nearest neighbors.
networkOfRoutines	Each unit agent had a bundle of routines (i.e., a certain specific vector with “0” or “1” values) to cope with its series of organizational subtasks. However, rather than being only a simple collection, these routines were interrelated with each other [11, 39], so giving rise to a network of routines. We assumed that this network was randomly generated [43, 72], as illustrated in Figure 1.
Fitness	The value of this parameter represented the adaptiveness of a unit agent to its living environment. In detail, we considered each routine’s fitness contribution function shown in formula (1) as a random function mapping the vector (where, and , , ) with uniformly distributed values fiti (0 ≤ fiti ≤ 1). Then, we assumed that the fitness value of the unit agent was numerically equal to the average of the fit value of all the routines involved (as shown in formula (2)).