A deterministic model of a research organization’s evolution and dynamics of performance

Abstract

Abstract Quantitative descriptions of complex social systems hold promise for many applications such as understanding and quantifying group behaviour, organizational performance and inter-personal interactions. Since social systems are interacting and evolving systems, dynamical modelling of them enables the possibility to study time evolution under different scenarios in a quantitative and possibly predictive framework. There are, however, several challenges in developing such dynamical models, one of which is that unlike in physical systems, it is difficult to identify unambiguous, let alone unique, casual relations in social dynamics. A further major difficulty is in quantifying attributes like performance, personal choice and leadership. Here, we provide such a quantitative model of a sociological system, namely a research organization, with its performance as a dynamical variable. We use the model to study the evolution and sensitivity of the performance of a research organization under different conditions. The performance is measured as the sum of contributions from the individual members of the organization in terms of metrics, such as number of research publications. The individual performances are driven by various benchmarks, personal goals and other processes that respond to time-dependent internal and external factors. The factors that arise from institutional and individual aspects, like institutional average and national benchmark, are represented mathematically to describe the dynamics. The model demonstrates complex behaviour that a research institution can exhibit in response to internal as well as external factors. The model is applied to quantify the roles of various processes like initial selection criteria and leadership response in the institutional dynamics and the categories of performers. The novel feature in our formalism is a somewhat mechanistic, and deterministic, description of a research organization’s evolution over time. Our results demonstrate that a social system such as a research organization can be modelled as an initial and boundary value dynamical system. Unlike qualitative or static models, such a dynamical model allows us to chart institutional trajectories under different organizational conditions. This concept and the methodology can be extended to other social systems—such as electorates or a publicly funded organization—with appropriate dynamical variables.