George Liberopoulos | Searcharxiv

arXiv2019

Retailer response to wholesale stockouts

The purpose of this paper is to identify the immediate and future retailer response to wholesale stockouts. We perform a statistical analysis of historical customer order and delivery data of a local tool wholesaler and distributor, whose customers are retailers, over a period of four years. We investigate the effect of customer service on the order fill rate and the rate of future demand, where the customer service is defined in terms of timely delivery and the fill rate is defined as the fraction of the order that is eventually materialized, i.e., is not cancelled following a stockout.We find that for customers who order frequently, stockouts have an adverse effect on the fill rate of their orders and on the frequency but not the value of their future demand; however, this latter effect seems to be more short-term than long-term. Practically all studies on the effects of stockouts measure immediate reported/intended consumer purchase incidence and choice decision behavior in response to stockouts in retail environments, mostly based on surveys. This study looks at how stockouts affect future demand in a wholesale environment, based on historical behavioral data analysis.

stat.AP↗

arXiv2019

Performance evaluation of a production line operated under an echelon buffer policy

We consider a production line consisting of several machines in series separated by intermediate finite-capacity buffers. The line operates under an "echelon buffer" (EB) policy according to which each machine can store the parts that it produces in any of its downstream buffers if the next machine is occupied. If the capacities of all but the last buffer are zero, the EB policy is equivalent to CONWIP. To evaluate the performance of the line under the EB policy, we model it as a queueing network, and we develop a method that decomposes this network into as many nested segments as there are buffers and approximates each segment with a two-machine subsystem that can be analyzed in isolation. For the case where the machines have geometrically distributed processing times, we model each subsystem as a two-dimensional Markov chain that can be solved numerically. The parameters of the subsystems are determined by relationships among the flows of parts through the echelon buffers in the original system. An iterative algorithm is developed to solve these relationships. We use this method to evaluate the performance of several instances of 5- and 10-machine lines including cases where the EB policy is equivalent to CONWIP. Our numerical results show that this method is highly accurate and computationally efficient. We also compare the performance of the EB policy against the performance of the traditional "installation buffer" policy according to which each machine can store the parts that it produces only in its immediate downstream buffer if the next machine is occupied.

eess.SY↗