Model Competition in a Work Place.
By: - Antonio Soares & Hiral Patel
PSYC 469/800 final project
By: - Antonio Soares & Hiral Patel
PSYC 469/800 final project
Properties of individual Agents
Project managers will be equidistant from each other and have an initial reach of 2x2 patches. Their position is fixed. Employees will populate randomly. The number of employees with each job will fit a 1:2:2 ratio, though this could be changed to represent the demand of particular positions. Clients have generated each time step are only present for a single iteration. Contracts will contain the number of each employee type required. The number required for each job type will follow the ratio but include some randomness. We will use 7 as the average demand, but the actual number will follow a normal distribution.
Agents Interaction Rules
Project managers (PMs) search for a client.
PMs will link with all the clients in their reach. If there is at least one client in the reach, the PM does not search for a client outside their reach. Otherwise, they find up to 1 client outside their reach.
Then PMs search for the employees needed to meet the demand.
Employees (and clients) within a project manager's reach are inaccessible to other project managers.
The project manager's reach increases by a radius of 1 if the contract is met, and decreases the same amount if it is not.
Employees will randomly move from 0-2 patches in any direction each time step if they are not in a successful contract. If they are in a successful contract, they will move 2 patches towards the PM.
Measures of Affinity or networking influence.
Simulation Plan
The average number of employees will be 20 with an SD of .5. This number will be multiplied by the ratio for the employee type. The number of clients will have an average of 5 and the average demand for each type will be 7 multiplied by the ratio for that employee type. The standard deviation for client number and demand will be varied from .5 to 1.5. 10 samples will be taken for each parameter setting. The average length of ticks before a PM takes over will be used to compare the conditions.
We predict that once a project manager has a large reach, other project managers will have trouble filling the needs of clients. On the other hand, if the reach is big enough to take too many clients, there is a chance for the other project managers to become the biggest. Varying the SD instead of mean is meant to produce more variability between ticks.
We aimed to show how client properties can affect the competition of project managers with fixed employees. The duration of the simulations indicate how readily previous success determines future success, therefore the failure of other managers. A shorter duration means that there is a positive feedback effect for success, while longer duration would not support that as much.
It was observed that a client SD of 1 most consistently produced a short duration.
Client SD of .5 generally has the longest duration, with the exception of client SD of 1.5 with a demand SD of .5.
Given that the demand SD of .5 has the longest duration in client SD of .5 and 1.5, it would suggest that client SD of 1 has some interaction effect with demand SD of .5.
In short, client SD of 1 produces a short duration. The longest duration is produced by demand SD of .5 except in client SD of 1.
The success of a project manager is largely determined by their relational connectedness with clients and employees. In this model, it is operationalized as reach and primarily influenced by success. In a virtual and highly interconnected environment, having strong influence or affinity with others is influential to success.
Other factors that can influence connectedness and success:
Employee resistance or confusion over the project guidelines.
Being less confident and doesn’t have a positive attitude to overcome challenges could affect the results.
1) Shethna, J. (2021, March 26). Affinity Groups in The Workplace: 8 Brilliant Features of Affinity Groups. EDUCBA. https://www.educba.com/affinity-groups-in-the-workplace/
2) Joshi, A. (2006). The influence of organizational demography on the external networking behavior of teams. The Academy of Management Review, 31(3), 583-595. doi:http://dx.doi.org/10.2307/20159230