Stochastic capacity management in the presence of production resource disruption

• Main Author: YANG, Boya
• Format: text
• Language: English
• Published: Institutional Knowledge at Singapore Management University 2020
• Subjects: stochastic capacity management; financial constraints; supply disruption; random capacity; sensitivity analysis; OM-Finance interface; Finance; Finance and Financial Management
• Online Access: https://ink.library.smu.edu.sg/etd_coll/292; https://ink.library.smu.edu.sg/cgi/viewcontent.cgi?article=1292&context=etd_coll
• Institution: Singapore Management University

This dissertation studies the capacity investment decision of a manufacturing firm facing demand uncertainty in the presence of shortage possibility in production resources, as often ignored in the literature. These production resources can be physical resources (component / raw material) or financial resources (working capital / budget). The shortage in these resources can be caused by a variety of supply chain disruptions; examples include global disruptions like COVID-19 and financial crisis in 2008 and local disruptions like shortage of components/workforce. The dissertation analyses two important issues related to capacity management: (i) the effect of production resource disruption on the capacity investment strategy and the profitability of the firm (including the significance of profitability loss incurred when the resource shortage possibility is ignored, and (ii) the role of production resource disruption management strategies, i.e. using pre-shipment financing to mitigate the effect of financial resource disruption and using hedging to mitigate physical resource disruption. The first part examines a two-stage capacity-production framework that capacity investment decision is in anticipation of demand and production resource uncertainties and production quantity is decided after the revelation of uncertainties. I characterize the optimal decisions and investigate how the uncertainties (demand and production resource variability and the correlation between the two) affect the optimal capacity investment level and profitability. My results provide a rule of thumb for the managers in capacity management. I also study the significance of profitability loss incurred when the resource uncertainty is ignored in choosing a capacity level. Through both analytical and extensive numerical analysis, I show that the profitability loss is high when 1) correlation is high; 2) either production resource variability is sufficiently high or sufficiently low; and 3) either demand variability is sufficiently high or sufficiently low. The second part examines the role of pre-shipment finance in managing financial production resource (working capital/budget) disruption. Pre-shipment finance allows the firm to transfer the purchase orders (which will be paid after production) to an external party that provides immediate cash flow (at a cost) that can be used for financing the production process. To this end, I characterize the optimal pre-shipment finance level (proportion of sales revenues transferred) and the production volume in the production stage and the optimal capacity investment level in the capacity stage. I make comparisons with the results in the first chapter to understand how pre-shipment financing alters the effects of demand and production resource uncertainties on the optimal capacity investment level, expected profit and profitability loss due to ignoring resource uncertainty. I identify that applying pre-shipment finance makes the capacity investment and profits more resilient to changes in spot price uncertainty. The third part studies the role of procurement hedging contract in managing physical production resource (e.g., component/raw material) disruption. With the hedging contract, the firm can engineer the production resource uncertainty at the capacity investment stage—for example, with full hedging this uncertainty can be completely removed. I provide the joint characterization of the optimal hedging level and capacity investment decisions. I find that these decisions critically depend on the covariance between demand and production resource uncertainties and the unit capacity investment cost. For example, I find that fully hedging is always optimal when the correlation is non-positive. I highlight conditions under which the firm optimally does not hedge at all or use partial hedging strategy. I then investigate the significance of the profitability loss due to i) misspecification of capacity level by ignoring production resource uncertainty and ii) misspecification of hedging strategy (using full hedging which is easy to implement), and provide conditions under which these profitability losses are significant.