Drivers of On-Time Delivery for Build-to-Stock Items: An Empirical Analysis of Time Series Data on Fill Rate Performance

33 Pages Posted: 13 Mar 2011

See all articles by David Xiaosong Peng

David Xiaosong Peng

University of Houston - C.T. Bauer College of Business

Shekhar Jayanthi

Rensselaer Polytechnic Institute (RPI)

Gregory R. Heim

Texas A&M University - Department of Information & Operations Management

Date Written: March 10, 2011

Abstract

Many firms today compete on their ability to deliver customer orders quickly and reliably. While researchers have proposed numerous factors believed to affect delivery performance, little empirical research has examined such factors using longitudinal data from real world manufacturing operations. This paper examines a list of structural, demand, and supply factors believed to impact delivery using monthly data on product assembly from a major manufacturer. We estimate econometric models that capture the impacts of these factors upon product line item fill rates. The findings provide support for several hypothesized drivers of delivery performance. Managers may benefit from the empirical approach and research findings, which identify salient variables that managers can monitor and adjust to ensure desired delivery outcomes.

Keywords: delivery performance, manufacturing operations, built-to-stock, operations strategy, supply chain uncertainties, regression, time-series data

JEL Classification: D2, D20, M11, M, L6

Suggested Citation

Peng, David Xiaosong and Jayanthi, Shekhar and Heim, Gregory R., Drivers of On-Time Delivery for Build-to-Stock Items: An Empirical Analysis of Time Series Data on Fill Rate Performance (March 10, 2011). Available at SSRN: https://ssrn.com/abstract=1783082 or http://dx.doi.org/10.2139/ssrn.1783082

David Xiaosong Peng (Contact Author)

University of Houston - C.T. Bauer College of Business ( email )

Houston, TX 77204-6021
United States

Shekhar Jayanthi

Rensselaer Polytechnic Institute (RPI) ( email )

Troy, NY 12180
United States

Gregory R. Heim

Texas A&M University - Department of Information & Operations Management ( email )

320 Wehner Building
4217 TAMU
College Station, TX 77843-4217
United States
979-845-9218 (Phone)

HOME PAGE: http://mays.tamu.edu/info/

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