Management Science

Gawande, Kishore; Bohara, Alok K.

doi: 10.1287/mnsc.1050.0422pmid: N/A

We study two issues in the enforcement of public law. The first is whether the system of inspections and penalties set by the regulator is effective. The second is whether a better system of inspections and penalties can be designed, given the institutional constraints under which the regulator must function. We study these issues in the context of oil spill prevention activities of the U.S. Coast Guard (USCG), the agency entrusted with the enforcement of maritime pollution laws. A theoretically optimal contract that mixes penalties based on the amount of pollution ex post with penalties based on the extent of noncompliance ex ante is derived. The effectiveness of USCG inspections and penalties in reducing oil spills is then econometrically studied using microlevel data on a panel of U.S. flag tank vessels. Whether the optimal penalty can potentially improve the effectiveness of compliance inspections in reducing oil spills is examined in the light of the empirical results and recent developments in the economics and public management literature on effective incentive contracting. Among our findings is the potential for combining unilateral incentive-based methods with cooperative methods based on reciprocity to solve the complex problem of law enforcement.

de Jong, Ad; de Ruyter, Ko; Wetzels, Martin

doi: 10.1287/mnsc.1050.0425pmid: N/A

This paper proposes and tests a model of antecedents and consequences of group potency in self-managing teams in retail banking. Based on data collected from boundary-spanning service employees organized in 60 teams and their customers, our findings reveal a significant positive impact of group potency on customer-perceived service quality and a negative effect on service profitability. In addition, we find that team consensus regarding group potency positively moderates the effects of group potency, so that for teams with higher levels of potency consensus, the positive impact of group potency on customer-perceived service quality is stronger, whereas the negative impact of group potency on service productivity is weaker. Furthermore, we find significant positive effects of management and interteam support and functional diversity as well as a significant negative effect of team tenure on individual team member beliefs of group potency. Finally, social support consensus moderates the effects of management support, interteam support, and team tenure on group potency, so that the effects of these antecedents are weaker for teams with higher levels of social support consensus. Thus, we conclude that team confidence consensus increases the positive impact of group potency on customer perceptions of service quality and decreases the negative impact on profitability. Thus, team-member perceptual agreement on their team's potency should be stimulated.

Kwon, Young K.

doi: 10.1287/mnsc.1050.0417pmid: N/A

There are two sources of agency costs under moral hazard: (1) distortions in incentive contracts and (2) implementation of suboptimal decisions. In the accounting literature, the relation between conservative accounting and agency costs of type (1) has received considerable attention (cf. Watts 2002). However, little appears to be known about the effects of accounting conservatism on agency costs of type (2) or trade-offs between agency costs of types (1) and (2). The purpose of this study is to examine this void. In a principal-agent setting in which the principal motivates the agent to expend effort using accounting earnings, this study shows that accounting earnings become more useful for reducing agency costs of type (2) when measured conservatively than when measured aggressively. Combined with the result in Kwon et al. (2001) that agency costs of type (1) decrease with accounting conservatism, this analysis suggests that conservative accounting enhances the incentive value of accounting signals with respect to both types of agency costs.

Gneezy, Uri

doi: 10.1287/mnsc.1050.0423pmid: N/A

Step-level models of reasoning (SLR) proved to be very successful in predicting behavior in the beauty contest game. Recently, a quantified version of the model was suggested as a more general model of thinking. In particular, it was found that the distribution of choices could be represented by a Poisson distribution. I test the model in stylized first- and second-price common-value sealed-bid auctions. Equilibrium, for both auction types, prescribes that players undercut each other and profits are small. The SLR prediction, on the other hand, is different for the two auctions. Nash equilibrium predicts the outcomes poorly; the SLR model predicts the outcomes well in the second-price auction. However, while bids in the first-price auction could be represented by a Poisson distribution, this could not be attributed to step-level reasoning.

Glasserman, Paul; Li, Jingyi

doi: 10.1287/mnsc.1050.0415pmid: N/A

Monte Carlo simulation is widely used to measure the credit risk in portfolios of loans, corporate bonds, and other instruments subject to possible default. The accurate measurement of credit risk is often a rare-event simulation problem because default probabilities are low for highly rated obligors and because risk management is particularly concerned with rare but significant losses resulting from a large number of defaults. This makes importance sampling (IS) potentially attractive. But the application of IS is complicated by the mechanisms used to model dependence between obligors, and capturing this dependence is essential to a portfolio view of credit risk. This paper provides an IS procedure for the widely used normal copula model of portfolio credit risk. The procedure has two parts: One applies IS conditional on a set of common factors affecting multiple obligors, the other applies IS to the factors themselves. The relative importance of the two parts of the procedure is determined by the strength of the dependence between obligors. We provide both theoretical and numerical support for the method.

Detemple, Jérôme; Garcia, René; Rindisbacher, Marcel

doi: 10.1287/mnsc.1050.0398pmid: N/A

We study the convergence of Monte Carlo estimators of derivatives when the transition density of the underlying state variables is unknown. Three types of estimators are compared. These are respectively based on Malliavin derivatives, on the covariation with the driving Wiener process, and on finite difference approximations of the derivative. We analyze two different estimators based on Malliavin derivatives. The first one, the Malliavin path estimator, extends the path derivative estimator of Broadie and Glasserman (1996) to general diffusion models. The second, the Malliavin weight estimator, proposed by Fournié et al. (1999), is based on an integration by parts argument and generalizes the likelihood ratio derivative estimator. It is shown that for discontinuous payoff functions, only the estimators based on Malliavin derivatives attain the optimal convergence rate for Monte Carlo schemes. Estimators based on the covariation or on finite difference approximations are found to converge at slower rates. Their asymptotic distributions are shown to depend on additional second-order biases even for smooth payoff functions.

Best, Michael J.; Hlouskova, Jaroslava

doi: 10.1287/mnsc.1050.0418pmid: N/A

We consider the problem of maximizing an expected utility function of n assets, such as the mean-variance or power-utility function. Associated with a change in an asset's holdings from its current or target value is a transaction cost. This cost must be accounted for in practical problems. A straightforward way of doing so results in a 3n-dimensional optimization problem with 3n additional constraints. This higher dimensional problem is computationally expensive to solve. We present a method for solving the 3n-dimensional problem by solving a sequence of n-dimensional optimization problems, which accounts for the transaction costs implicitly rather than explicitly. The method is based on deriving the optimality conditions for the higher-dimensional problem solely in terms of lower-dimensional quantities. The new method is compared to the barrier method implemented in Cplex in a series of numerical experiments. With small but positive transaction costs, the barrier method and the new method solve problems in roughly the same amount of execution time. As the size of the transaction cost increases, the new method outperforms the barrier method by a larger and larger factor.

Klose, Andreas; Drexl, Andreas

doi: 10.1287/mnsc.1050.0410pmid: N/A

The capacitated facility location problem (CFLP) is a well-known combinatorial optimization problem with applications in distribution and production planning. A variety of lower bounds based on Lagrangean relaxation and subgradient optimization has been proposed for this problem. However, information about a primal (fractional) solution can be important to solve large or difficult problem instances. Therefore, we study various approaches for solving the master problems exactly. The algorithms employ different strategies for stabilizing the column-generation process. Furthermore, a new lower bound for the CFLP based on partitioning the plant set and employing column generation is proposed. Computational results are reported for a set of large problem instances.

van Hoesel, Stan; Romeijn, H. Edwin; Morales, Dolores Romero; Wagelmans, Albert P. M.

doi: 10.1287/mnsc.1050.0378pmid: N/A

We consider a model for a serial supply chain in which production, inventory, and transportation decisions are integrated in the presence of production capacities and concave cost functions. The model we study generalizes the uncapacitated serial single-item multilevel economic lot-sizing model by adding stationary production capacities at the manufacturer level. We present algorithms with a running time that is polynomial in the planning horizon when all cost functions are concave. In addition, we consider different transportation and inventory holding cost structures that yield improved running times: inventory holding cost functions that are linear and transportation cost functions that are either linear, or are concave with a fixed-charge structure. In the latter case, we make the additional common and reasonable assumption that the variable transportation and inventory costs are such that holding inventories at higher levels in the supply chain is more attractive from a variable cost perspective. While the running times of the algorithms are exponential in the number of levels in the supply chain in the general concave cost case, the running times are remarkably insensitive to the number of levels for the other two cost structures.

Andersen, Kent; Cornuéjols, Gérard; Li, Yanjun

doi: 10.1287/mnsc.1050.0382pmid: N/A

Mixed-integer Gomory cuts have become an integral part of state-of-the-art software for solving mixed-integer linear programming problems. Therefore, improvements in the performance of these cutting planes can be of great practical value. In this paper, we present a simple and fast heuristic for improving the coefficients on the continuous variables in the mixed-integer Gomory cuts. This is motivated by the fact that in a mixed-integer Gomory cut, the coefficient of an integer variable lies between 0 and 1, whereas for a continuous variable, there is no upper bound. The heuristic tries to reduce the coefficients of the continuous variables. We call the resulting cuts reduce-and-split cuts. We found that on several test problems, reduce-and-split cuts can substantially enhance the performance of a branch-and-bound algorithm.