I want to develop a forecasting model for OES transmission filters to
automotive dealership service departments.  What I am looking for is a
robust list of independent variables (predictor variables) that would
be potential factors for this forecasting model and also a way to
capture or measure these variables.

Background Information to Aid the Researcher:

The automotive transmission filter market can be divided into the
following categories:  Original Equipment (OE) and Aftermarket (but I
am not looking at the aftermarket).   OE filters consist of those
filters originally installed on a new vehicle.  Within the OE sector,
a subdivision is realized:  Original Equipment Manufactured (OEM) and
Original Equipment Supplied (OES).
 
?	OEM filters: those filters originally installed on a new vehicle.  
?	OES filters: those filters used when maintenance is required after
the vehicle leaves the plant.   These are typically available at the
service departments of automobile dealerships.

The closest article I have found is listed below:

Clay, G. & Grange, F. (1997). Evaluating forecasting algorithms and
stocking level   strategies using discrete-event simulation. 
Proceeding of the 1997 Winter Simulation Conference.

I have also managed to locate the following book:

Naples, G. (1994). By the Numbers: Principles of Automotive Parts
Management.  Society of Automotive Engineers.

Additional sources I have identified include:
Original Equipment Suppliers Association (OESA)
Council for Logistics Management
AIAG
IRN
Supply Chain Council
Economist Intelligence Unit
Institute of Business Forecasting