This study seeks to examine how the quantitative semantics of the learning curve phenomenon can be employed in order to derive monetary information for team learning observed within knowledge‐intensive production environments.
Software development is selected as an identical example of a team‐based, knowledge‐intensive production environment. The interaction of learning rate of the developer teams and the improvements on their average solving time (i.e. productivity) is modelled as a Lotka‐Volterra predator‐prey interacting populations system establishing a causal relationship between the human capital (HC) of organizational teams and the observed learning curve effects on their performance. In addition, empirical evidence illustrates that the estimated learning rates capture the entire range of team learning effects on performance fluctuations caused by the HC.
The fluctuations on the learning rates can be interpreted as a result of the HC variability across the population of developer teams. Hence, the cost implications of the HC within knowledge‐intensive production environments can be rationalised using the quantitative semantics of the learning curve phenomenon
The learning curve is associated with the cost side of the organizational income‐generating process limiting its potential valuation applications for team learning observed within the context of the production environments.
The study offers a theoretical justification, supported by empirical evidence, for employing the mathematical expression of the learning curve paradigm to rationalize the financial consequences of team learning observed within production environments.
