A Newsvendor Approach to Compliance and Production under Cap and Trade Emissions Regulation

Since the 1990s, governmental agencies have increasingly turned to market based cap and trade programs to control the emission of pollutants. Firms subject to cap and trade regulation are typically required to acquire emissions allowances via open auction markets. The cost to acquire allowances may impose a substantial financial burden on a firm. While emissions reduction efforts may eliminate some firm\u27s need to acquire additional allowances, there are still numerous firms that need to purchase additional allowances on the open market. This study presents a new forward buying heuristic, designed for those firms that need to purchase emissions allowances via auctions, which reduces the impact of emissions allowance acquisitions on the firms\u27 financial performance. The heuristic, designated as the Newsvendor Production Planning with Emissions Allowance Forward Buying (NPPAFB) method, applies a forward buying algorithm to determine the number of periods for which to forward buy allowances, the current production order up to level, and the current and future emissions allowance requirements (which serves as the order up to level for allowance purchases). Additionally, NPPAFB also authorizes unused emissions allowances to be sold when market conditions are favorable. Compared against three existing production planning and allowance procurement strategies, a simulation exercise finds that the NPPAFB method significantly reduces a firm\u27s emissions allowance expenditures. These results indicate that heuristic can be readily adopted by any firm that is required to procure emissions allowances via open markets in an effort to improve the firm\u27s profitability

Essays in inventory decisions under uncertainty

Uncertainty is a norm in business decisions. In this research, we focus on the inventory decisions for companies with uncertain customer demands. We first investigate forward buying strategies for single stage inventory decisions. The situation is common in commodity industry where prices often fluctuate significantly from one purchasing opportunity to the next and demands are random. We propose a combined heuristic to determine the optimal number of future periods a firm should purchase at each ordering opportunity in order to maximize total expected profit when there is uncertainty in future demand and future buying price. Second, we study the complexities of bundling of products in an Assemble-To-Order (ATO) environment. We outline a salvage manipulator mechanism that coordinates the decentralized supply chain. Third, we extend our salvage manipulator mechanism to a two stage supply chain with a long cumulative lead time. With significant lead times, the assumption that the suppliers all see the same demand distribution as the retailer cannot be used.Ph.D.Committee Chair: Yih-Long Chang; Committee Member: Paul Griffin; Committee Member: Ravi Subramanian; Committee Member: Soumen Ghosh; Committee Member: Srinagesh Gavirnen

Essays on Stochastic Inventory Systems

University of Minnesota Ph.D. dissertation. July 2015. Major: Industrial and Systems Engineering. Advisor: Saif Benjaafar. 1 computer file (PDF); ix, 147 pages.This thesis consists of three essays in stochastic inventory systems. The first essay is on the impact of input price variability and correlation on stochastic inventory systems. For a general class of such systems, we show that the expected cost function is concave in the input price. From this, it follows that higher input price variability in the sense of the convex order always leads to lower expected cost. We show that this is true under a wide range of assumptions for price evolution, including cases with i.i.d. prices and cases where prices are correlated and evolve according to an AR(1) process, a geometric Brownian motion, or a Markovian martingale. In addition, the result holds in cases where there is just a single period. We also examine the impact of price correlation over time and across inputs, and we find that expected cost is increasing in price correlation over time and decreasing in price correlation across components. We present results of a numerical study that provide insights on how various parameters influence the effects of price variability and correlation. The second essay is on the optimal control of inventory systems with stochastic and independent leadtimes. We show that a fixed base-stock policy is sub-optimal and can perform poorly. For the case of exponentially distributed leadtimes, we show that the optimal policy is state-dependent and specified in terms of an inventory-dependent threshold function. Moreover, we show that this threshold function is non-increasing in the inventory level and characterized by at most m parameters. That is, once the threshold function starts to decrease it continues to decrease with a rate that is at least one. Taking advantage of this structure, we develop an efficient algorithm for computing these parameters. In characterizing the structure of the optimal policy, we rely on an application of the Banach fixed point theorem. We compare the performance of the optimal policy to that of simpler heuristics. We also extend our analysis to systems with lost sales and systems with order cancellations. The third essay is on the optimal policies for inventory systems with concave ordering costs. By extending the Scarf (1959} model to systems with piecewise linear concave ordering costs, we characterize the structure of optimal policies for periodic review inventory systems with concave ordering costs and general demand distributions. We show that, except for a bounded region, the generalized (s,S) policy is optimal. We do so by (a) introducing a conditional monotonicity property for the optimal order-up-to levels and (b) applying the notion of c-convexity. We also provide conditions under which the generalized (s, S) policy is optimal for all regions of the state space

Contemporary working capital practices in australia

Corporate finance focuses on investment and financing decisions. Within this framework, however, the finance literature has given little consideration to working capital management. Similarly, in practice, working capital managers are regarded as passive contributors to major business decisions. This thesis attempts to increase academic awareness of the importance of working capital management. When we combine the existing literature with recent events, such as industrial technological advances, changes in Australian accounting standards, and the global financial crisis, a fertile research ground is evident and allows us to explore current practices in working capital management. Data are collected through interviews with 10 corporate treasurers and a survey of 120 Australian corporations to document the approaches used by working capital managers in the areas of cash, inventory, accounts receivable, accounts payable, and risk management. This thesis reports how fundamental factors such as firm size, company performance, credit ratings, industry, and education, gender, and age of the working capital manager play a vital role in the management of these areas. This paper’s major contribution lies in its examination of the behavioural aspects of working capital managers. We show that Australian managers are prone towards behavioural biases such as loss aversion, overconfidence, anchoring, and self-serving biases, and that some of these can be desirable for efficiency. Taking into account all of these factors, we propose a profile of a good working capital manager

Service Inventory Management : Solution techniques for inventory systems without backorders

Koole, G.M. [Promotor]Vis, I.F.A. [Copromotor