Showing papers by "Andrew L. Johnson published in 2014"

Nonparametric measurement of productivity and efficiency in education

Abstract: Nondiscretionary environmental inputs are critical in explaining relative efficiency differences and productivity changes in public sector applications. For example, the literature on education production shows that school districts perform better when student poverty is lower. In this paper, we extend the nonparametric approach to decompose the Malmquist Productivity Index suggested by Fare et al. (American Economic Rewiew 84:66–83, 1994) into efficiency, technological and environmental changes. The approach is applied to analyze educational production of Ohio school districts. Applying the extended approach in an analysis of the educational production of 604 school districts in Ohio, we find changes in environmental harshness are the primary drivers in productivity changes of underperforming school districts, while technical progress drives the performance of top performing school districts.

Reviewing the literature on non-parametric dynamic efficiency measurement: state-of-the-art

Abstract: Much of the literature on static efficiency measurement models assumes that the inputs are fully used for producing outputs in the same period, with the result that no time interdependence exists between the input utilization and output realizations for a production unit in consecutive periods. A review of the literature on non-parametric dynamic efficiency models identifies five key factors of the inter-temporal dependence between input and output levels over different periods: (i) production delays; (ii) inventories (inventories of exogenous inputs or inventories of intermediate and final products); (iii) capital or generally quasi-fixed factors (and associated embodied technological change, vintage specific capital); (iv) adjustment costs; and (v) incremental improvement and learning models (disembodied technological change). This paper reviews the literature and finds that the dynamic issues associated with adjustment costs and capital have received considerable attention in the literature, whereas the dynamic issues associated with inventories have received less attention. The paper concludes with suggestions for future research such as relaxing the perfect anticipation/knowledge assumption for future variables, prices, and states. Moreover, Dynamic Network Data Envelopment Analysis has provided a unifying framework for some dynamic factors, but further development of these models is necessary including meaningful applications.

Multilateral contracting and prevention.

Abstract: Incentives created through contracts can be used as a means of decentralized control in healthcare systems to ensure more efficient healthcare. In this paper, we consider an insurer contracting with a consumer and a provider. We focus on the trade-off between ex ante moral hazard and insurance, and consider both consumer and provider incentives in the insurer's contracting problem in the presence of unobservable preventive efforts. We study two cases of provider efforts: those that complement consumer efforts and those that substitute for consumer efforts. In the first case, our results show that the provider must have greater incentives when the consumer is healthy to induce effort and that inducing provider effort allows an insurer to offer a more complete insurance contract relative to the bilateral benchmark. In the second case, we state conditions under which these conclusions continue to hold. On the basis of our findings, we discuss the implications and challenges of multilateral contracting in practice. Copyright © 2013 John Wiley & Sons, Ltd.

Order Batching With Time Constraints in a Parallel-aisle Warehouse: a Multiple-policy Approach

Abstract: A commitment of delivery time is critical in some online businesses (De Koster, 2003). An important challenge to meeting customers’ needs is timely order picking which is also relevant to worker safety, item freshness, overall operational synchronization, and reduced overtime. We analyze an order batch picking situation where a trip is constrained by vehicle capacity and must be completed within a specified time. We develop a model which partitions orders to batches to minimize the total travel time such that each trip meets the orders’ time constraints and capacity limit, and also determines a suitable operational policy for each batch. Each policy is characterized by routing method, travel speed, capacity, and pick time. The proposed batching model can simultaneously group orders and can select a best policy among possible policy choices