A discrete time Markov chain model for a periodic inventory system with one-way substitution.

This paper studies the optimal design of an inventory system with “one-way substitution”, in which a high-quality (and hence, more expensive) item fulfills its own demand and simultaneously acts as backup safety stock for the (cheaper) low-quality item. Through the use of a discrete time Markov model we analyze the effect of one-way substitution in a periodic inventory system with an (R,s,S) or (R,S) order policy, assuming backorders, zero replenishment leadtime and correlated demand. In more detail, the optimal inventory control parameters (S and s) are determined in view of minimizing the expected total cost per period (i.e. sum of inventory holding costs, purchasing costs, backorder costs and adjustment costs). Numerical results show that the one-way substitution strategy can outperform both the “no pooling” (only product-specific stock is held, and demand can never be rerouted to stock of a different item) and “full pooling” strategies (implying that demand for a particular product type is always rerouted to the stock of the flexible product, and no product-specific stock is held) − provided the mix of dedicated and flexible inputs is chosen adequately − even when the cost premium for flexibility is significant. Furthermore, we can observe that decreasing the demand correlation results in rerouting more demand to the flexible product and because of the risk-pooling effect reduces the optimal expected total cost.Inventory management; One-way substitution;

The value of SKU rationalization: the pooling effect under suboptimal inventory policies

Managing product variety is a widely recognized challenge. Several approaches to this rely on the "pooling effect", the reduction of uncertainty that occurs when individual demands are aggregated. This can occur through reduction of number of products orSKUs, through postponement of differentiation, or in other ways. These approaches are by now well-known and widely applied in practice. However, theoretical analyses of the pooling effect always assume that one has an optimal inventory policy before and after pooling. If this is not the case, how does that affect the value of pooling? This paper analyses the benefits of pooling in terms of costs and service level under optimal and suboptimal policies and proposes a simple framework to analyze the trade-off between implementing pooling and improving inventory policy. We show there is always a range of current inventory levels within which pooling is better and beyond whichoptimizing inventory policy is better. We analyze how this range varies with the problem parameters and illustrate these findings using highly erratic empirical demand data

An Empirical Study of Operational Performance Parity Following Enterprise System Deployment

This paper presents an empirical investigation into whether the implementation of packaged Enterprise Systems (ES) leads to parity in operational performance. Performance change and parity in operational performance are investigated in three geographically defined operating regions of a single firm. Order lead time, the elapsed time between receipt of an order and shipment to a customer, is used as a measure of operational performance. A single ES installation was deployed across all regions of the subject firm\u27s operations.Findings illustrate parity as an immediate consequence of ES deployment. However, differences in rates of performance improvement following deployment eventually result in significant (albeit smaller than pre-deployment) performance differences. An additional consequence of deployment seems to be an increased synchronization of performance across the formerly independent regions

Partial pooling by independent firms with allocation according to contribution to pool

We consider two firms which pool some of their inventory. The pool is created by the firms' contributions, and a firm's entitlement for an allocation from the pool (if needed) is a function of its contribution. Transshipment from the pool is costly, but the firms can benefit from reduced risk through inventory sharing using the pool. We analyze the resulting non-cooperative game. We prove existence of a Nash equilibrium and compare it to a model with centralized control. An appropriate compensation cost for using the other firms contribution to the pool can induce the retailers to achieve centralized solutions. We also compare the optimal partial pooling strategy to the special cases of no pooling and complete pooling and discuss situations where it is likely that one of the special cases will be optimal. Numerical results confirm that in the prevalent practice of partial pooling the retailers can achieve higher expected profits than under no pooling or complete pooling and that there is a significant difference between a setting with independent players and a model of central control

On two-echelon inventory systems with Poisson demand and lost sales

We derive approximations for the service levels of two-echelon inventory systems with lost sales and Poisson demand. Our method is simple and accurate for a very broad range of problem instances, including cases with both high and low service levels. In contrast, existing methods only perform well for limited problem settings, or under restrictive assumptions.\u

Inventory Signals

How does operational competence translate into market value, when firms cannot credibly communicate their competence to the market? I consider the example of inventory and fill rates. When the market sees a high-inventory firm, it cannot tell whether the inventory is due to incompetence or a strategy to enhance fill rate. Firms might decide to signal their competence to the market by carrying less inventory. I show conditions for separating and pooling perfect Bayesian equilibria. I also provide empirical evidence for this theory that inventory has a signaling role. The theory could potentially provide a framework that describes one way in which a range of operational competences such as purchasing and outsourcing, translate to market value. Practically, it has implications for firms, such as how to strategically communicate to the market, reward managers, or even whether to go public and be subject to market pressures.Inventory; signaling; operations management; asymmetric information

Teaching operations management using a 'pseudo'-scientific approach

The purpose of this paper is to explore a theory led approach to teaching operations and supply chain management that has emerged from the analysis of seminal operations management developments and case research. This research identified common operations construct relationships encompassing variation, uncertainty, buffering mechanisms and trade-offs which are used to provide a common basis for explaining these developments, linking established theory with current professional practice. The construct relationships are further shown to comprise three distinct but coordinated strategies that provide a useful framework for case evaluatio

Characterization and Modeling of Spectrum Trading Markets

Telecommunication regulators are facing increasing pressure to make spectrum resources more widely available to new wireless services and providers. In spectrum trading markets, buyers and sellers determine the assignments of spectrum and, possibly, its uses. These markets are being considered or implemented by the regulatory bodies of many countries as a way to provide increasing efficiency in the use of spectrum and attend the demand for this resource. This work describes a classification for the implementation of spectrum trading markets and a way to model them and identify the conditions for their viability. Specifically, we make use of Agent-Based Computational Economics (ACE) to model the participants in these markets, analyze the behaviors that emerge from the interactions of its participants and determine the conditions for viable markets. Our results, provide guidelines that can be used by regulators and wireless service providers for the design and implementation of these markets

Evolutionary multiobjective optimization of the multi-location transshipment problem

We consider a multi-location inventory system where inventory choices at each location are centrally coordinated. Lateral transshipments are allowed as recourse actions within the same echelon in the inventory system to reduce costs and improve service level. However, this transshipment process usually causes undesirable lead times. In this paper, we propose a multiobjective model of the multi-location transshipment problem which addresses optimizing three conflicting objectives: (1) minimizing the aggregate expected cost, (2) maximizing the expected fill rate, and (3) minimizing the expected transshipment lead times. We apply an evolutionary multiobjective optimization approach using the strength Pareto evolutionary algorithm (SPEA2), to approximate the optimal Pareto front. Simulation with a wide choice of model parameters shows the different trades-off between the conflicting objectives