| Summary: | This research designs a purchasing decision support system (PDSS) to assist
real-world decision makings on whether to purchase or to sub-hire for
equipment shortfalls problem, and to avoid shortage loss for rental business.
Research methodology includes an extensive literature review on decision
support systems, rental industry, and forecasting methods. A case study was
conducted in a rental company to learn the real world problem and to develop
the research topics. A data converter is developed to recover the missing data
and transform data sets to the accumulative usage data for the forecasting
model.
Simulations on a number of forecasting methods was carried out to select the
best method for the research data based on the lowest forecasting errors. A
hybrid forecasting approach is proposed by adding company revenue data as a
parameter, in addition to the selected regression model to further reduce the
forecasting error. Using the forecasted equipment usage, a two stage PDSS
model was constructed and integrated to the forecasting model and data
converter.
This research fills the gap between decision support system and rental industry.
The PDSS now assists the rental company on equipments buy or hire decisions.
A hybrid forecasting method has been introduced to improve the forecasting
accuracy significantly. A dada converter is designed to efficiently resolve data
missing and data format problems, which is very common in real world.
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