Knowledge sharing assessment: An Ant Colony System based Data Envelopment Analysis approach

Knowledge sharing as one of the most crucial processes in knowledge management, operates in a dynamic environment. Dedicated tools to measure its performance under such an environment are not found in the literature. This paper aims to fill this void by proposing a hybrid model based on Data Envelopment Analysis (DEA). Monte Carlo simulation is incorporated into the model to handle stochastic data. In addition, to improve the model’s accuracy, the Ant Colony System (ACS) metaheuristic is blended with Monte Carlo simulation and DEA. The model is named ACS-DEA and is found to be able to increase the accuracy and reliability of the results. Although this model aims to assess knowledge sharing performance, it could also be used in other relevant fields in dynamic settings.

► A Data Envelopment Analysis model is devised to assess knowledge sharing.
► Monte Carlo simulation is utilized to handle stochastic data.
► Ant Colony System is used to obtain an efficient data collection plan.
► With Ant Colony System, the accuracy of the results has been improved.