A stochastic model to optimize forecast and fulfillment of green roof demand

Increasing demand for green roofs in cities has generated pressure on the landscape industry to supply materials in a timely manner. A demand-responsive optimal-inventory model (DOM) is developed to predict future demand and optimize contractor inventories of green roof components. Unlike other operations research models, no assumption is made on demand distribution. Instead, a stochastic model is constructed based on building owners' behavior and two pertinent extrinsic factors: changing government incentive policy and increasing energy price. When actual demand exceeds predicted value, undesirable backorder and inventory shortfall emerge. The reverse scenario creates superfluous inventories and elevated holding cost. As managers have scanty market data for the relatively new products, they use current demand to predict next-period demand. The findings suggest adopting the safe lower limit of demand fluctuations to prevent overstocking. The numerical experiment finds the greatest demand fluctuations in the first year of the government reimbursement program. The sensitivity analysis indicates sensitive response of green-roof accumulated demand to extrinsic influences. Managers could regularly update demand forecast and inventory strategy to dovetail with changing market and policy environment. The stochastic model could capture most of the important real-world features of the green-roof market by relatively simple mathematical expressions. Copyright © 2012 Elsevier GmbH. All rights reserved.