Should an OEM Retain Component Procurement when the CM Produces Competing Products?

We consider a large original equipment manufacturer (OEM) who relies on a contract manufacturer (CM) to produce her product. In addition to the OEM's product, the CM also produces for a smaller OEM. Both the larger OEM and the CM can purchase the component from the supplier, but their purchase prices may differ and remain unknown to each other. The main question we address is whether the larger OEM should retain component procurement by purchasing components from the supplier and reselling to the CM (buy–sell), or outsource component procurement by letting the CM purchase directly from the supplier (turnkey). We show that, under buy–sell, the larger OEM's optimal strategy is to resell components at the highest possible component purchase price of the CM (i.e., the street price). By comparing buy–sell and turnkey, we find that a CM with low component price is better off under turnkey, even though under buy–sell he receives more profits through the products sold to the smaller OEM. Furthermore, the larger OEM's preference between buy–sell and turnkey depends on her component price, the volatility of the CM's component price and substitutability between the two products.     

A Sales Forecast Model for Short‐Life‐Cycle Products: New Releases at Blockbuster

We develop, in this article, a sales model for movie and game products at Blockbuster. The model assumes that there are three sales components: the first is from consumers who have already committed to purchasing (or renting) a product (e.g., based on promotion of, or exposure to, the product prior to its launch); the second comes from consumers who are potential buyers of the product; and the third comes from either a networking effect on closely tied (as in a social group) potential buyers from previous buyers (in the case of movie rental and all retail products) or re‐rents (in the case of game rental). In addition, we explicitly formulate into our model dynamic interactions between these sales components, both within and across sales periods. This important feature is motivated by realism, and it significantly contributes to the accuracy of our model. The model is thoroughly tested against sales data for rental and retail products from Blockbuster. Our empirical results show that the model offers excellent fit to actual sales activity. We also demonstrate that the model is capable of delivering reasonable sales forecasts based solely on environmental data (e.g., theatrical sales, studio, genre, MPAA ratings, etc.) and actual first‐period sales. Accurate sales forecasts can lead to significant cost savings. In particular, it can improve the retail operations at Blockbuster by determining appropriate order quantities of products, which is critical in effective inventory management (i.e., it can reduce the extent of over‐stocking and under‐stocking). While our model is developed specifically for product sales at Blockbuster, we believe that with context‐dependent modifications, our modeling approach could also provide a reasonable basis for the study of sales for other short‐Life‐Cycle products.     

Impact of Reseller's Forecasting Accuracy on Channel Member Performance

This article studies a three‐layer supply chain where a manufacturer sells a product through a reseller who then relies on its own salesperson to sell to the end market. The reseller has superior capability in demand forecasting relative to the manufacturer. We explore the main trade‐offs between the risk‐reduction effect and the information–asymmetry–aggravation effect of the improved forecasting accuracy. We show that under the optimal wholesale price contract, both the manufacturer and the reseller are always better off as the reseller's forecasting accuracy improves. Nevertheless, under the menu of two‐part tariffs, the manufacturer prefers the reseller to be either uninformed or perfectly informed about the market condition. We further find that the improved forecasting accuracy is beneficial for the reseller if its current forecasting system is either very poor or very good.     

AN INTERNATIONAL COMPARISON OF LIFETIME INEQUALITY: HOW CONTINENTAL EUROPE RESEMBLES NORTH AMERICA

We compare earnings inequality and mobility across the United States, Canada, France, Germany and the United Kingdom during the late 1990s. A flexible model of earnings dynamics that isolates positional mobility within a stable earnings distribution is estimated. Earnings trajectories are then simulated, and lifetime annuity value distributions are constructed. Earnings mobility and employment risk are found to be positively correlated with base‐year inequality. Taken together they produce more equalization in countries with high cross‐section inequality such that the countries in our sample have more similar lifetime inequality levels than cross‐section measures suggest.     

COMPETITION AND RELATIONAL CONTRACTS: THE ROLE OF UNEMPLOYMENT AS A DISCIPLINARY DEVICE

Abstract When workers are faced with the threat of unemployment, their relationship with a particular firm becomes valuable. As a result, a worker may comply with the terms of a relational contract that demands high effort even when performance is not enforceable by a third party. But can relational contracts motivate high effort when workers can easily find alternative jobs? We examine how competition for labor affects the emergence of relational contracts and their effectiveness in overcoming moral hazard in the labor market. We show that effective relational contracts do emerge in a market with excess demand for labor. Long‐term relationships turn out to be less frequent when there is excess demand for labor than they are in a market characterized by exogenous unemployment. However, stronger competition for labor does not impair labor market efficiency: higher wages induced by competition lead to higher effort out of concerns for reciprocity.     

Inventory Policy with Parametric Demand: Operational Statistics,Linear Correction,and Regression

In this paper, we consider data‐driven approaches to the problem of inventory control. We first consider the approach of operational statistics and review related results which enable us to maximize a priori expected profit uniformly over all parameter values, when the demand distribution is known up to the location and scale parameters. For the case of the unknown shape parameter, we first suggest a heuristic approach based on operational statistics to obtain improved ordering policies and illustrate the same for the case of a Pareto demand distribution. In more general cases where the heuristic is not applicable, we suggest linear correction and support vector regression approaches to better estimate ordering policies, and illustrate these using a Gamma demand distribution. In certain cases, our proposed approaches are found to yield significant improvements.     

An Application of Master Schedule Smoothing and Planned Lead Time Control

Make‐to‐order (MTO) manufacturers must ensure concurrent availability of all parts required for production, as any unavailability may cause a delay in completion time. A major challenge for MTO manufacturers operating under high demand variability is to produce customized parts in time to meet internal production schedules. We present a case study of a producer of MTO offshore oil rigs that highlights the key aspects of the problem. The producer was faced with an increase in both demand and demand variability. Consequently, it had to rely heavily on subcontracting to handle production requirements that were in excess of its capacity. We focused on the manufacture of customized steel panels, which represent the main sub‐assemblies for building an oil rig. We considered two key tactical parameters: the planning window of the master production schedule and the planned lead time of each workstation. Under the constraint of a fixed internal delivery lead time, we determined the optimal planning parameters. This improvement effort reduced the subcontracting cost by implementing several actions: the creation of a master schedule for each sub‐assembly family of the steel panels, the smoothing of the master schedule over its planning window, and the controlling of production at each workstation by its planned lead time. We report our experience in applying the analytical model, the managerial insights gained, and how the application benefits the oil‐rig producer.     

Newsvendor Pricing Problem in a Two‐Sided Market

We study the pricing problem of a “platform” intermediary to jointly determine the selling price of the platforms (hardware) sold to consumers and the royalty charged to content developers for content (software), when the demands for content and for platforms are interdependent. Our model elucidates the impact of supply chain replenishment costs and demand uncertainty on the strategic issues of platform pricing in a two‐sided market.     

Container Scheduling: Complexity and Algorithms

We consider the transport of containers through a fleet of ships. Each ship has a capacity constraint limiting the total number of containers it can carry and each ship visits a given set of ports following a predetermined route. Each container has a release date at its origination port, and a due date at its destination port. A container has a size 1 or size 2; size 1 represents a 1 TEU (20‐foot equivalent unit) and size 2 represents 2 TEUs. The delivery time of a container is defined as the time when the ship that carries the container arrives at its destination port. We consider the problem of minimizing the maximum tardiness over all containers. We consider three scenarios with regard to the routes of the ships, namely, the ships having (i) identical, (ii) nested, and (iii) arbitrary routes. For each scenario, we consider different settings for origination ports, release dates, sizes of containers, and number of ports; we determine the computational complexity of various cases. We also provide a simple heuristic for some cases, with its worst case analysis. Finally, we discuss the relationship of our problems with other scheduling problems that are known to be open.