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This paper shows that operational flexibility interacting with informational uncertainty may lead to truthful information exchange in equilibrium even when the communication is nonbinding and unverifiable, i.e., 'cheap talk.' We consider a model consisting of a manufacturer releasing a new product with uncertain release date and demand, and a retailer who must determine the allocation of limited capacity between a preexisting third-party product and the manufacturer's new product that may or may not be released on time. The manufacturer has a private forecast about the likelihood of the product release and/or about the demand, which he shares (either truthfully or not) with the retailer. We show that under the 'traditional' supply chain structure (one-time opportunity to order) no truthful equilibrium can emerge. However, if (1) the supply chain structure allows for postponement, i.e., the ability to delay orders at a certain cost by the retailer, and (2) the manufacturer has informational uncertainty about the retailer's capacity, then truthful information exchange may emerge in equilibrium, where the manufacturer transmits his true forecast and the retailer treats the transmission as truthful. The genesis of this effect is preference reversal, where the manufacturer is not sure which way to distort the forecast to best motivate the retailer to wait for the new product. Thus, we show that a truth-revealing mechanism can emerge from a relatively rich setup featuring two-sided information asymmetry interacting with postponement. History: Accepted by Gad Allon, operations management. Keywords: forecast information sharing * cheap talk * supply chain flexibility * postponement * procurement timing, 1. Introduction Coordination between different levels of a supply chain is critical for the chain to operate effectively (see, e.g., Byrnes and Shapiro 1991, Kurt Salmon Associates 1993). One of [...]

This paper, motivated by a collaboration with a healthcare service provider, focuses on stochastic open-shop service networks with two objectives: more traditional macrolevel measures (such as minimizing total system time or minimizing total number of tardy customers) and the atypical microlevel measure of reducing the incidents of excessively long waits at any workstation within the process. While work-conserving policies are optimal for macrolevel measures, scheduling policies with strategic idleness (SI) might be helpful for microlevel measures. Using the empirical data obtained from the service provider, we provide statistical evidence that SI is used by its schedulers to manage the macro- and microlevel measures. However, the company has no specific rules on implementing SI and the schedulers make decisions based on their own experience. Our primary goal is to develop a systematic framework for the joint usage of SI with dynamic scheduling policies (DSPs). We suggest to use threshold-based policies to intelligently combine SI and DSPs and show that the resulting policies provide an efficient way to simultaneously address both macro- and microlevel measures. We build two simulation models: one based on empirical data and one based on a randomly generated open-shop network. We use both models to demonstrate that an open-shop service network can be systematically and effectively managed to deliver improved service level by using SI. Funding: The first three authors acknowledge financial support from their respective Natural Sciences and Engineering Research Council of Canada grants. Supplemental Material: The online appendix is abailable at https://doi.org/10.1287/msom.2016.0591. Keywords: strategic idleness * dynamic scheduling policy * open shop * healthcare * service network, 1. Introduction In this paper, we focus on stochastic open-shop processes operating under multiple objectives. The system objectives include a combination of the more traditional macrolevel measures (such as minimizing [...]

In this paper we develop a service network design model that explicitly takes into account the elasticity of customer demand with respect to travel distance and congestion delays. The model [...]

We analyze the problem of optimal location of a set of facilities in the presence of stochastic demand and congestion. Customers travel to the closest facility to obtain service; the [...]

Business schools look for ways to teach MBA graduates effective group work skills, generally through group-based assignments and projects. However, if not monitored carefully, group work can undermine the learning [...]

In this paper we address a basic problem that arises naturally in average-reward Markov decision processes with constraints and/or nonstandard payoff criteria: Given a feasible state-action frequency vector ('the target'), [...]

The Hamiltonian Cycle Problem and the Traveling Salesman Problem were studied and characterized using an unconventional approach. The two combinatorial optimization problems were embedded in suitably controlled Markov chains before they were subsequently subjected to numerical analysis. This approach results in the introduction of a quadratic entropy-like function which can then be solved using the global solution of the indefinite quadratic program.