This study applies an agent-based modeling approach to explore some aspects of an important managerial task: finding and cultivating talented individuals capable of creating value for their organization at some future state. Given that the term talent in talent management is an empty signifier and its denotative meaning floating, we propose that bounded rational managers base their decisions on a simple heuristic, i.e. selecting and cultivating individuals so that their capabilities resemble their own capabilities the most (Adamsen 2015). We model the consequences of this talent management heuristic by varying the capabilities of today’s managers, which in turn impact which individuals will be selected as talent. We model the average level of capabilities and the distribution thereof in the sample where managers identify and select individuals from. We consider varying degrees of path dependency of the organizations’ success by assuming that some organizations will become successful in the future by replicating what they did to become successful in the past (Silzer &Dowell.2010; Capelli.2008). Other organizations’ past success is assumed to become obsolete, which means that replication of past success will provide failure rather than success in the future (Capelli.2008). Finally, we model the talent selection process either as a collective decision making process made by a group of managers or a decision process made by a single manager.It is argued that agent-based modeling is a useful method for studying this type of problems. The approach is particularly suitable to topics where understanding processes and their consequences is important. Agent-based models can include agents that are heterogeneous in their features and abilities, and can deal directly with the consequences of interaction between agents (Gilbert, 2008). Social systems where dependencies among the agents are important have been referred to as complex systems. The field of complex systems challenges the notion that by perfectly understanding the behavior of each component part of a system we will then understand the system as a whole (Miller & Scott, 2007). Agent-based simulations are well-suited to studying complex systems by examining how interactions between multiple heterogeneous agents cause structures at a higher level of aggregation to emerge as a result of their interaction over time (Siggelkow & Rivkin, 2006). Another strong feature of the agent-based modeling approach in the social sciences is that it allows the researcher to run controlled experiments in an isolated system and observing what happens. The great advantage of experiments is that they allow one to be sure that it is the researcher’s intervention that is causing the observed effects. A computer simulation is an abstract representation of something in the real social world. Deriving the behavior of a simulation model analytically is useful because it provides information about how the model will behave given a range of inputs, and by experimenting with different inputs it is possible to learn how the model behaves. The model is used to simulate the real world as it might be in a variety of circumstances (Gilbert, 2008). For this study a simulation model coded in Java-based NetLogo language was created. The simulation model contained only the features essential to this problem as intentional simpli-fication is strongly endorsed in modeling approaches (e.g. Axelrod, 1997; Gilbert, 2008). The simulation model allowed us to explore how the interplay of the model’s variables played out and together impacted the organization’s performance over time. The considered variables were: (a) decision makers’ attributes (capabilities and degree of bounded rationality), (b) characteristics of the sample where individuals are selected from (the level of capabilities and the dispersion thereof), (c) path-dependency of the organization’s success, and (d) the decision making process as either individual or collective. The results from a series of experiments with the model suggest that … Discussions of the findings, the contribution to theory, the managerial implications, the limitations, and suggestions for future research finalize the paper.
|Number of pages||2|
|Publication status||Published - 2015|
|Event||AISB Workshop : Agent-based models of bounded rationality - SDU Slagelse, Slagelse, Denmark|
Duration: 7. May 2015 → 8. May 2015
|Period||07/05/2015 → 08/05/2015|