Behavioral Implications of Demand Perception in Inventory Management

The newsvendor problem is one of the rudimentary problems of inventory management with significant practical consequences, thus receiving considerable attention in the behavioral operational research literature. In this chapter, we focus on how decision makers perceive demand uncertainty in the newsvendor setting and discuss how such perception patterns influence commonly observed phenomena in order decisions, such as the pull-to-center effect. Drawing from behavioral biases such as over precision, we propose that decision makers tend to perceive demand to be smaller than it actually is in high margin contexts, and this effect becomes more pronounced with increases in demand size. The opposite pattern is observed in low margin settings; decision makers perceive demand to be larger than the true demand, and this tendency is stronger at lower mean demand levels. Concurrently, decision makers tend to perceive demand to be less variable than it actually is, and this tendency propagates as the variability of demand increases in low margin contexts and decreases in high margin contexts. These perceptions, in turn, lead to more skewed decisions at both ends of the demand spectrum. We discuss how decision makers can be made aware of these biases and how decision processes can be re-designed to convert these unconscious competencies into capabilities to improve decision making

On the incomplete results for the heterogeneous server problem

In this article, we show that the arguments in Rykov [9] on the optimality of a threshold routing policy when there are more than two heterogeneous servers are incomplete. © Springer Science + Business Media, LLC 2006.link_to_subscribed_fulltex

Managing response time in a call-routing problem with service failure

Traditional research on routing in queueing systems usually ignores service quality related factors. In this paper, we analyze the routing problem in a system where customers call back when their problems are not completely resolved by the customer service representatives (CSRs). We introduce the concept of call resolution probability, and we argue that it constitutes a good proxy for call quality. For each call, both the call resolution probability (p) and the average service time (1/μ.) are CSR dependent. We use a Markov decision process formulation to obtain analytical results and insights about the optimal routing policy that minimizes the average total time of call resolution, including callbacks. In particular, we provide sufficient conditions under which it is optimal to route to the CSR with the highest call resolution rate (pμ,) among those available. We also develop efficient heuristics that can be easily implemented in practice.link_to_subscribed_fulltex

Stock rationing in a multi-class make-to-stock queue with information on the production status

International audienc

Stock rationing in a multi-class make-to-stock queue with information on the production status

International audienc

Critical Level Policies in Lost Sales Inventory Systems with Different Demand Classes

International audienceWe consider a single-item lost sales inventory model with different classes of customers. Each customer class may have different lost sale penalty costs. We assume that the demands follow a Poisson process and we consider a single replenishment hypoexponential server. We give a Markov decision process associated with this optimal control problem and prove some structural properties of its dynamic programming operator. This allows us to show that the optimal policy is a critical level policy. We then discuss some possible extensions to other replenishment distributions and give some numerical results for the hyperexponential server case

Multilevel rationing policy for spare parts when demand is state dependent

The multilevel rationing (MR) policy is the optimal inventory control policy for single-item M / M / 1 make-to-stock queues serving different priority classes when demand rate is constant and backlogging is allowed. Make-to-repair queues serving different fleets differ from make-to-stock queues because in the setting of the former, each fleet comprises finitely many machines. This renders the characterization of the optimal control policy of the spare part inventory system difficult. In this paper, we implement the MR policy for such a repair shop/spare part inventory system. The state-dependent arrival rates of broken components at the repair shop necessitate a different queueing-based solution for applying the MR policy from that used for make-to-stock queues. We find the optimal control parameters and the cost of the MR policy; we, then compare its performance to that of the hybrid FCFS and hybrid priority policies described in the literature. We find that the MR policy performs close to the optimal policy and outperforms the hybrid policies