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Special Issue on Data Science for Better Productivity

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

ORCID Icon, ORCID Icon &
Pages 1015-1032 | Received 06 Aug 2018, Accepted 12 Jan 2020, Published online: 06 Feb 2020
 

Abstract

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.

Disclosure statement

No potential conflict of interest was reported by the authors.

Additional information

Funding

This article was funded by Ministry of Science and Technology [MOST 107-2410-H-606-005-MY3].

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