Efficient Resource Allocation Via Efficiency Bootstraps: An Application to R&D Project Budgeting

Operations Research, Vol. 59, No. 3, pp. 729-741, 2011

Posted: 31 Aug 2010 Last revised: 10 May 2013

See all articles by Chien-Ming Chen

Chien-Ming Chen

Nanyang Technological University (NTU) - Nanyang Business School

Joe Zhu

affiliation not provided to SSRN

Date Written: August 30, 2010

Abstract

Resource allocation decisions are crucial for the survival success of an organization. This paper proposes an integrated approach to resource allocation problems, in which decision-makers have one observation of the multiple input-output criteria of candidates. We offer important improvements over existing approaches based on the widely used data envelopment analysis (DEA), which has two major limitations in its application to resource allocation. First, traditional DEA models compute efficiency scores by optimizing firm-specific shadow prices of inputs and outputs. This could be problematic because in practice stakeholders would usually require unanimously agreed trade-offs among evaluation criteria. Second, previous allocation approaches based on DEA do not allow for controlling the risk exposure of allocation portfolios. To tackle these problems, we propose an efficiency measure based on equilibrium shadow prices of different criteria, and use the bootstrap efficiency distributions to gather information regarding efficiency variations and correlations. Through our methodology, decision makers can obtain the risk minimizing allocation portfolio. We illustrate the proposed approach through an empirical R&D project budgeting problem, in which we allocate funding according to the projects efficiency distributions.

Keywords: productivity, data envelopment analysis, decision-making

JEL Classification: C15, C44

Suggested Citation

Chen, Chien-Ming and Zhu, Joe, Efficient Resource Allocation Via Efficiency Bootstraps: An Application to R&D Project Budgeting (August 30, 2010). Operations Research, Vol. 59, No. 3, pp. 729-741, 2011. Available at SSRN: https://ssrn.com/abstract=1668704

Chien-Ming Chen (Contact Author)

Nanyang Technological University (NTU) - Nanyang Business School ( email )

Singapore, 639798
Singapore

Joe Zhu

affiliation not provided to SSRN ( email )

Here is the Coronavirus
related research on SSRN

Paper statistics

Abstract Views
566
PlumX Metrics