This study utilizes linear programming and regression for identifying distributors of Tennessee Valley Authority (TVA) power that deviate from the normal efficiency levels and for listing distributor attributes that affect these efficiencies. The conclusions are: (1) most TVA distributors are...

Despite advances in retail point-of-sale (POS) data sharing, retailers’ suppliers struggle to effectively use POS data to improve their fulfillment planning processes. The challenge lies in predicting retailer orders. We present evidence that retail echelon inventory processes translate into a...

The application of the human capital theory, the production theory, and the comparison of costs between teaching and non-teaching hospitals all point to the difficulties in identifying whether medical residents should be considered as inputs or outputs. We add to the debate by using a...

We propose a set of consistency conditions that frontier efficiency measures should meet to be most useful for regulatory analysis or other purposes. The efficiency estimates should be consistent in their efficiency levels, rankings, and identification of best and worst firms; consistent over...

This paper uses a stochastic cost frontier to examine the scale economies, cost efficiencies, and technological change of three payments instruments--check, automated clearinghouse (ACH) transfers, and Fedwire processing--provided by the Federal Reserve over the period 1990-94. We find evidence...

This paper examines the properties of the X-inefficiencies in U.S. bank holding companies derived from both stochastic and linear programming frontiers. This examination allows the robustness of results across methods to be compared. While we find that calculated programming inefficiency scores...

We propose a set of consistency conditions that frontier efficiency measures should meet to be most useful for regulatory analysis or other purposes. The efficiency estimates should be consistent in their efficiency levels, rankings, and identification of best and worst firms, consistent over...