A comparison between the robust risk-aware and risk-seeking managers in R&D portfolio management

Shuyi Wang () and Aurélie Thiele ()
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Shuyi Wang: Alliance Data
Aurélie Thiele: Southern Methodist University

Computational Management Science, 2017, vol. 14, issue 2, No 2, 197-213

Abstract: Abstract In this paper, we analyze two mathematical modeling frameworks that reflect different managerial attitudes toward upside risk in the context of R&D portfolio selection. The manager seeks to allocate a development budget between low-risk, low-reward projects, called incremental projects, and high-risk, high-reward projects, called innovational projects. Because of their highly uncertain nature and significant probability of failure, the expected value of the innovational projects is smaller than that of their incremental projects’ counterpart, but the long-term financial health of a company necessitates to take risk in order to maintain growth. We study the differences in strategy and portfolio’s risk profile that arise between a risk-aware manager, who takes upside risk because he has to for the long-term competitive advantage of his company, and a risk-seeking manager, who will take as big a bet as allowed by the model. To the best of our knowledge, this is the first paper to consider upside risk management using a robust-optimization-like methodology.

Keywords: Upside risk; Robust optimization; R & D portfolio management (search for similar items in EconPapers)
Date: 2017
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Citations: View citations in EconPapers (1)

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DOI: 10.1007/s10287-016-0271-4

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