Int. J. Operational Research, Vol. 3, No. 6, 2008 681 Copyright © 2008 Inderscience Enterprises Ltd. Risk averse selective newsvendor problems Kevin Taaffe* and Kiran Chahar Department of Industrial Engineering, Clemson University, 110 Freeman Hall, Clemson, SC 29634, USA E-mail: taaffe@clemson.edu E-mail: kchahar@clemson.edu *Corresponding author Deepak Tirumalasetty TransSolutions, LLC, 14600 Trinity Blvd., Suite 200, Ft. Worth, TX 76155, USA E-mail: deepak@transsolutions.com Abstract: Consider a firm that offers a product during a single selling season. The firm has the flexibility of choosing which demand sources to serve, but these decisions must be made prior to knowing the actual demand that will materialise in each market. Moreover, we assume that the firm operates on a tight budget and cannot afford to record several successive financial losses spanning consecutive periods. In this case, it is likely that their objective is not only to maximise expected profit, but also to minimise the variance from that goal. We provide insights into the tradeoff between expected profit and demand uncertainty using a mean variance approach. We also present a solution approach, via simulation, to determine a market set (and total order quantity) when the firm’s objective is to minimise the probability of receiving a profit below a critical threshold value. Keywords: demand selection; demand uncertainty; heuristic; mean variance analysis; newsvendor; order quantity; risk aversion; simulation. Reference to this paper should be made as follows: Taaffe, K., Chahar, K. and Tirumalasetty, D. (2008) ‘Risk averse selective newsvendor problems’, Int. J. Operational Research, Vol. 3, No. 6, pp.681–703. Biographical notes: Kevin Taaffe is an Assistant Professor in the Department of Industrial Engineering at Clemson University. He has been conducting research primarily in the areas of production and inventory management, transportation and logistics systems analysis and emergency evacuation. The main focus of his research is in addressing how stochastic behaviour in real-world systems can be modelled and accounted for appropriately in planning and analysis. He is a Senior member of IIE as well as a member of INFORMS, Transportation Research Board and Decision Sciences Institute.