Online Program Home
  My Program

Abstract Details

Activity Number: 165 - Statistics for Business and Financial Markets
Type: Contributed
Date/Time: Monday, July 31, 2017 : 10:30 AM to 12:20 PM
Sponsor: Business and Economic Statistics Section
Abstract #323232 View Presentation
Title: Validating a Time Series Model for Supply Chain Inventory Data
Author(s): Morris Morgan* and Carolyn Bradshaw Morgan and Eric Abram Morgan and Kristin Morgan
Companies: Hampton University and MECK Limited,LLC and St. Michael's Inc. and University of Connecticut
Keywords: Time Series ; ARIMA ; Inventory ; Supply Chain ; Robust ; Forecast Estimates

Supply chain inventory models quite often play a major role in the development of effective business strategies that impact profitability. These models are essential to effective business management. The focus of the current inquiry is operational and thus we are interested in identifying correlations among events occurring during a narrowly defined business cycle. In the present context, we will use appropriate Box and Jenkins methodologies to devise robust time series models that are parsimonious and reliable and possess decidability.

Specially, this paper revisits two business questions posed by a client regarding inventory data. In a recent paper, Morgan et. al. (2016) revealed some interesting trends within that inventory data. Now, armed with additional out-year data, a new model will be developed and the results validated. In addition, the implications of the model results on real-time hiring and employment demands, as well aiding in the development of a potential training tool for new hires, will be outlined. As with the initial inquiry, the research will be directed at developing an adequate time series that represents monthly variation in inventory demand.

Authors who are presenting talks have a * after their name.

Back to the full JSM 2017 program

Copyright © American Statistical Association