Entrusting decisions to the public service pension fund: An integrated predictive model with additive network DEA approach

A critical issue for ensuring long-term sustainability of pension funds is how the Public Service Pension Fund Management Board (PSPFMB) makes entrusting decisions to choose investment trust corporations (ITCs). To design a more comprehensive performance measure, this study uses the additive network data envelopment analysis (DEA) approach to measure efficiency scores of 34 ITCs, including operating performance, equity fund performance, and bond fund performance. We further propose a method to effectively forecast the future efficiency scores of each ITC by using a trend analysis technique. Our mechanism for ITC evaluation helps improve the deficiency of old decision-making processes that merely look at ITCs' past performances. Our proposed approach offers a theoretical contribution to the additive DEA literature by through its practicality and by integrating measurement and prediction procedures. For a practical implication with additive network DEA, we provide a more feasible method for selecting ITCs that will run the Public Service Pension Fund.

Automated summary

This study employs the additive network DEA approach to measure efficiency scores of 34 ITCs and proposes a method to effectively forecast future efficiency scores using trend analysis technique. The mechanism helps improve decision-making processes and offers a more feasible method for selecting ITCs.