Explore the vast range of titles available.

Combinatorial allocation involves assigning bundles of items to agents when the use of money is not allowed. Course allocation is one common application of combinatorial allocation, in which the bundles are schedules of courses and the assignees are students. Existing mechanisms used in practice have been shown to have serious flaws, which lead to allocations that are inefficient, unfair, or both. A recently developed mechanism is attractive in theory but has several features that limit its feasibility for practice. This paper reports on the design and implementation of a new course allocation mechanism, Course Match, that is suitable in practice. To find allocations, Course Match performs a massive parallel heuristic search that solves billions of mixed-integer programs to output an approximate competitive equilibrium in a fake-money economy for courses. Quantitative summary statistics for two semesters of full-scale use at a large business school (the Wharton School of Business, which has about 1,700 students and up to 350 courses in each semester) demonstrate that Course Match is both fair and efficient, a finding reinforced by student surveys showing large gains in satisfaction and perceived fairness.

In this paper, I justify neutral mechanisms as the reasonable solutions for public good provision and cost shares in public goods problems. I illustrate that neutral mechanisms can be easily computed by the tractable set of conditions with straightforward interpretations for a class of public goods problems. I show that, unlike neutral mechanisms, ex ante incentive efficient mechanisms are not robust to a perturbation of the information structure at the time of mechanism selection. I highlight several merits of using neutral mechanisms instead of interim incentive efficient mechanisms: Neutral mechanisms yield sharp predictions, are invulnerable to the possibility of information leakage during the selection process, and have the attractive properties of both efficiency and equity. I discuss implications for the analysis of ex ante and interim incentive efficient mechanisms for public goods problems.

We consider a manufacturer selling to a retailer with private demand information arising dynamically over an infinite time horizon. Under a backlogging model, we show that the manufacturer’s optimal dynamic long-term contract takes a simple form: in the first period, based on her private demand forecast, the retailer selects a wholesale price and pays an associated upfront fee, and, from then on, the two parties stick to a simple wholesale price contract with the retailer’s chosen price. Under a lost sales model, we show that the structure of the optimal long-term contract combines a menu of wholesale pricing contracts with an option that, if exercised by the retailer, reduces future wholesale prices in exchange for an immediate payment to the manufacturer. The online appendix is available at https://doi.org/10.1287/opre.2017.1626 .

This paper investigates the role of time in forecast information sharing and decision making under uncertainty. To do so, we provide a general framework to model the evolutions of forecasts generated by multiple decision makers who forecast demand for the same product. We also model the evolutions of forecasts when decision makers have asymmetric demand information and refer to it as the Martingale Model of Asymmetric Forecast Evolutions . This model helps us study mechanism design problems in a dynamic environment. In particular, we consider a supplier's (principal's) problem of eliciting credible forecast information from a manufacturer (agent) when both firms obtain asymmetric demand information for the end product over multiple periods. The supplier uses demand information to better plan for a capacity investment decision. When the supplier postpones building capacity and screening the manufacturer's private information, the supplier and the manufacturer can obtain more information and update their forecasts. This delay, however, may increase (respectively, decrease) the degree of information asymmetry between the two firms, resulting in a higher (respectively, lower) cost of screening. The capacity building cost may also increase because of a tighter deadline for building capacity. Considering all such trade-offs, the supplier has to determine (i) when to stop obtaining new demand information and build capacity, (ii) whether to offer a screening contract to credibly elicit private forecast information or to determine the capacity level without information sharing, (iii) how much capacity to build, and (iv) how to design the overall mechanism so that both firms benefit from this mechanism. This paper provides an answer to these questions. In doing so, we develop a new solution approach for a class of dynamic mechanism design problems. In addition, this paper provides a framework to quantify the option value of time for a strategic investment decision under the dynamic evolutions of asymmetric forecasts. This paper was accepted by Yossi Aviv, operations management.

There is rich literature on using continuous-time and discrete-time models for studying population dynamics of consumer-resource interactions. A key focus of this contribution is to systematically compare between the two modeling formalisms the stabilizing/destabilizing impacts of diverse ecological processes that result in a density-dependent consumer attack rate. Inspired by the Nicholson-Bailey/Lotka-Volterra models in discrete-time/continuous-time, respectively, we consider host-parasitoid interactions with an arbitrary parasitoid attack rate that is a function of both the host/parasitoid population densities. Our analysis shows that a Type II functional response is stabilizing in both modeling frameworks only when combined with other mechanisms, such as mutual interference between parasitoids. A Type III functional response is by itself stabilizing, but the extent of attack-rate acceleration needed is much higher in the discrete-time framework, and its stability regime expands with increasing host reproduction. Finally, our results show that while mutual parasitoid interference can stabilize population dynamics, cooperation between parasitoids to handle hosts is destabilizing in both frameworks. In summary, our comparative analysis systematically characterizes diverse ecological processes driving stable population dynamics in discrete-time and continuous-time consumer-resource models.

We consider the problem of locating a facility on a network represented by a graph. A set of strategic agents have different ideal locations for the facility; the cost of an agent is the distance between its ideal location and the facility. A mechanism maps the locations reported by the agents to the location of the facility. We wish to design mechanisms that are strategyproof (SP) in the sense that agents can never benefit by lying and, at the same time, provide a small approximation ratio with respect to the minimax measure. We design a novel \"hybrid\" strategyproof randomized mechanism that provides a tight approximation ratio of 3/2 when the network is a circle (known as a ring in the case of computer networks). Furthermore, we show that no randomized SP mechanism can provide an approximation ratio better than 2 - o (1), even when the network is a tree, thereby matching a trivial upper bound of two.

Field tests were conducted on two new information aggregation mechanism designs. The mechanisms were designed to collect information held as intuitions about opening weekend box office revenues for movies in Australia. The principles on which the mechanisms operate and their capacity to collect information are explored. A pari-mutuel mechanism produces a predicted probability distribution over box office amounts that is, with the exception of very small films, indistinguishable from the actual revenues. The second mechanism is based on guessing the guesses of others and when applied under conditions where incentives for accuracy are unavailable still performs well against data.

Ideally, the properties of an economic mechanism should hold in a robust way across multiple equilibria and under varying assumptions regarding the information available to participants. Focusing on the design of robust position auctions, we seek mechanisms that possess an efficient equilibrium and guarantee high revenue in every efficient equilibrium, under complete and incomplete information. A generalized first-price auction that is expressive in the sense of allowing multidimensional bids turns out to be the only standard design able to achieve this goal, even when valuations are one dimensional. The equilibria under complete information are obtained via Bernheim and Whinston’s profit target strategies, those under incomplete information via an appropriate generalization thereof. Particularly interesting from a technical perspective is the incomplete information case, where the standard technique for establishing equilibrium existence due to Myerson is generalized to a setting in which the bid space has higher dimension than the valuation space.

Corporate digital transformation, primarily driven by data and leveraging digital technologies and mathematical algorithms such as Internet+, big data, cloud computing, artificial intelligence, and blockchain, is a crucial enabler of sustainable development. This transformation integrates various aspects of corporate production and operations, enhancing the level of digital operations and ultimately contributing to high-quality and sustainable development. This paper, based on data from listed companies in China’s A-shares from 2007 to 2021, theoretically articulates the intrinsic mechanism between corporate digital transformation and corporate governance level, with a focus on sustainability. It empirically finds that a higher degree of digital transformation correlates with an improved level of corporate governance, fostering sustainable practices. Further investigation reveals that digital transformation elevates corporate governance by enhancing innovation capabilities, reducing information asymmetry, and promoting sustainable strategies. This paper provides policy insights for promoting corporate digital transformation as a means to achieve sustainability goals and optimizing management’s corporate governance level for long-term sustainable success.

Notch flexure hinges are often used as revolute joints in high-precise compliant mechanisms, but their contour-dependent deformation and motion behaviour is currently difficult to predict. This paper presents general design equations for the calculation of the rotational stiffness, maximal angular elastic deflection and rotational precision of various notch flexure hinges in dependence of the geometric hinge parameters. The novel equations are obtained on the basis of a non-linear analytical model for a moment and a transverse force loaded beam with a variable contour height. Four flexure hinge contours are investigated, the semi-circular, the corner-filleted, the elliptical, and the recently introduced bi-quadratic polynomial contour. Depending on the contour, the error of the calculated results is in the range of less than 2 % to less than 16 % for the suggested parameter range compared with the analytical solution. Finite elements method (FEM) and experimental results correlate well with the predictions based on the comparatively simple and concise design equations.