A master production scheduling procedure for stochastic demand and rolling planning horizons

The problem of interest is a one product, uncapacitated master production schedule (MPS) in which decisions are made under rolling planning horizons. Demand is stochastic and time varying, and effectiveness is measured by inventory holding, production setup, and backorder costs.Typically, in both the research literature and the business practice the stochastic nature of the problem is modeled in an ad hoc fashion. The stochastic MPS problem is usually solved by adding safety stock to production quantities obtained from a deterministic lot-sizing algorithm. Here, the stochastic nature of the problem is explicitly considered, as an optimal algorithm for solving the static probabilistic dynamic lot-sizing problem is adapted to rolling planning horizons. The resulting algorithm is found to dominate traditional approaches over a wide variety of experimental factors, reducing total costs by an average of 16% over traditional methods.     

On scale economies and exhaustible resource markets

This paper considers an exhaustible resource market where firms realize economies of scale in the production of the resource, and may augment reserves through exploration. With the non-convexities inherent in this model, the typical firm's optimal decisions are corner solutions. It either operates at full intensity or not at all. Firms with larger current reserves have a greater incentive to produce today; firms with smaller reserves will tend to hold their reserves for production at a later date. It follows that the market supply curve in any given period is a step function. As price rises, production increases discontinuously: at discrete intervals, the marginal firm will change from not producing today to producing all of its reserves. With such a supply curve, the market may or may not clear. Simulation of this model suggests: (i) the chance of market clearing in any period is near 1/2; (ii) such an industry is unlikely to exhibit a significant increase in concentration over time.     

Media substitution and economies of scale in advertising

Two important issues in the economics of advertising are media substitutability in generating sales and scale economies in advertising. If media are substitutes then partial bans, e.g., broadcast bans on cigarettes or alcoholic beverages, may be ineffective; and mergers among radio and TV firms, currently widespread in the U.S. and Mexico, are unlikely to result in market power in setting advertising rates. If there are scale diseconomies in advertising, concerns that advertising increases entry barriers may be unfounded. Using U.S. beer firm data over 1983:Q1–1993:Q4 for three media categories, we find evidence of high substitutability and diseconomies of scale.     

Interfirm differences in scale economies and the evolution of market shares

Evolutionary and resource‐based theories imply that firms in an industry with different resources and capabilities may differ in critical characteristics of their production functions, such as economies of scale. This paper measures these inter‐firm differences in economies of scale and examines how they affect the subsequent evolution of the market share distribution in the money market mutual fund industry. The findings indicate that fund families with larger marginal benefits to increasing their scale do subsequently gain market share at the expense of their rivals, but that this effect diminishes as the fund family ages, perhaps as a consequence of imitation. Copyright © 1999 John Wiley & Sons, Ltd.     

Cellular economies of scale and why disparities in spectrum holdings are detrimental

Now that traffic volumes are increasing rapidly, the cost of expanding capacity has become a large portion of expenditures for Mobile Network Operators (MNOs). This paper uses an engineering-economic model to show that there are strong economies of scale when expanding capacity, because an MNO with more spectrum benefits more from every new cell tower, and an MNO with more towers benefits more from every new MHz of spectrum. While it is technically possible to expand capacity by increasing either towers or spectrum holdings, we find that the cost-effective approach is to increase both types of assets at a similar rate. In the absence of countervailing policies, the big MNOs are well positioned to get bigger, in terms of spectrum holdings, towers, and ultimately market share. For policymakers, this economy of scale creates a trade-off between two important objectives: reducing the cost of cellular capacity, and increasing competition. This paper derives the Pareto optimal division of spectrum with respect to these two competing objectives, and shows that any Pareto optimal assignment will split the spectrum fairly evenly among competing MNOs. This is not simply a method of ensuring that there are many competitors; spectrum should be divided fairly evenly regardless of whether the number of competitors is large or small. A large disparity in spectrum holdings may yield poor results with respect to both objectives, i.e. the lower cost-effectiveness of a larger number of MNOs, and the lower competitive pressure of a smaller number of MNOs. One effective way to achieve a division of spectrum that is close to Pareto optimal is a spectrum cap, provided that this cap is set at a level consistent with other policies and policy objectives, including antitrust policy.     

Budget allocation for permanent and contingent capacity under stochastic demand

We develop a model of budget allocation for permanent and contingent workforce under stochastic demand. The level of permanent capacity is determined at the beginning of the horizon and is kept constant throughout, whereas the number of temporary workers to be hired must be decided in each period. Compared to existing budgeting models, this paper explicitly considers a budget constraint. Under the assumption of a restricted budget, the objective is to minimize capacity shortages. When over-expenditures are allowed, both budget deviations and shortage costs are to be minimized. The capacity shortage cost function is assumed to be either linear or quadratic with the amount of shortage, which corresponds to different market structures or different types of services. We thus examine four variants of the problem that we model and solve either approximately or to optimality when possible. A comprehensive experimental design is designed to analyze the behavior of our models when several levels of demand variability and parameter values are considered. The parameters consist of the initial budget level, the unit cost of temporary workers and the budget deviation penalty/reward rates. Varying these parameters produce several trade-offs between permanent and temporary workforce levels, and between capacity shortages and budget deviations. Numerical results also show that the quadratic cost function leads to smooth and moderate capacity shortages over the time periods, whereas all shortages are either avoided or accepted when the cost function is linear.     

Estimating scale economies of the wireless telecommunications industry using EVA data

This paper proposes a new estimation method of total cost and average cost curves and applies it to the telecommunications industry. The method is more flexible and entails less hassle for data collection than traditional methods. The results show that the long-run average cost (LRAC) curve is downward sloping, revealing the presence of economies of scale in production. The two largest Korean mobile network operators are realizing full economies of scale, while the smallest operator is not. Finally, the paper recommends three policy alternatives that the Ministry of Information and Communication of Korea can draw on to increase efficiency in the Korean mobile telecommunications market.     

Productivity,scale economies and technical progress in the Canadian life insurance industry

The purpose of this paper is to examine the productivity performance of the Canadian life insurance industry. We construct a measure of total factor productivity for life insurance companies and then attempt to determine the main sources of improved productivity during the period 1961–1977 by pooling time-series and cross-section data from 31 firms. We conclude that for the industry as a whole technical progress was by far the most important source of productivity growth, while scale economies, on balance, had a marginally negative impact.     

Experience and scale and scope economies: trade‐offs and performance in development

This paper examines how knowledge created by firm experience (learning economies) and scale and scope economies affect performance in firms' development activities. The empirical results suggest that each factor has a significant effect on development performance. Moreover, knowledge that results from greater experience within a particular technological area, when combined with knowledge spillovers from greater scope in other technological areas, significantly improves development performance. The results suggest that experience shapes and facilitates firms' abilities to absorb knowledge spillovers. Our empirical findings thus provide a more nuanced examination of the drivers of performance and have implications for the management of firms' development activities. Copyright © 2006 John Wiley & Sons, Ltd.     

Technical change,competition and vertical integration

This paper starts with a survey of the received theories of vertical integration. We then extend these theories by arguing that while uncertainty in general will make integration more effective, a particular type of uncertainty, the possibility of technological obsolescence, works the other way. After making this point at a conceptual level, we build a model to study how the frequency of technological change interacts with the intensity of competition to influence the optimal level of integration. The predictions of the model are then tested and very strongly supported by data from 93 industries.     

Climatic change and food production

Small changes in climate can have a disproportionate influence on the availability of food when, as now, world reserves are low. Dr Gribbin reviews evidence for climatic change and concludes that the climate is likely to be much more variable in future than it has been in the middle decades of this century. Longer periods of unfavourable weather in some of the major agricultural areas are expected. Prudence dictates that world grain stocks should be built up as an insurance against an increasingly probable series of poor harvests.     

Robust optimal policies of production and inventory with uncertain returns and demand

We consider an inventory and production planning problem with uncertain demand and returns, in which the product return process is integrated into the manufacturing process over a finite planning horizon. We first propose an inventory control model for the return and remanufacturing processes with consideration of the uncertainty of the demand and returns. Then a robust optimization approach is applied to deal with the uncertainty of the problem through formulating a robust linear programming model. Moreover, properties on the robust optimization model are studied, and an equivalent robust optimization model based on duality theory is obtained which allows the solutions to be derived more efficiently. Finally, we provide a set of numerical examples to verify the effectiveness of the approach and analyze the effects of the key parameters on the solutions.     

A production rate control policy for stochastic repair and remanufacturing systems

We consider the control of a manufacturing system responding to planned demand at the end of the expected life of each individual piece of equipment and unplanned demand triggered by a major equipment failure. The difficulty of controlling this type of production system resides in the variable nature of the remanufacturing process. In practice, remanufacturing operations for planned demand can be executed at different rates, referring to different component replacement and repair strategies. We formulate this problem as a multi-level control problem and propose a suboptimal control policy. The proposed control policy is described by inventory thresholds triggering the use of different execution modes. Determination of the control policy parameters is based on parameter optimization of analytical cost expressions. A numerical example based on a real case is presented. Our analysis demonstrates that the use of the proposed control approach can lead to a significant reduction in the total average cost, as compared to current practices.     

An extended production/recycling model with stationary demand and return rates

A production–recycling system is investigated. A constant demand can be satisfied with production and recycling. The used items are bought back and then recycled. The non-recycled products are disposed of. Two types of models will be analyzed. The first model examines the EOQ-related costs and minimizes the relevant costs. The second model generalizes the first model with the introduction of the cost function with linear waste disposal, recycling, production and buyback costs. It is asked whether the pure (either production or recycling) or mixed strategies are optimal and it will be shown that under these circumstances the mixed strategies are dominated by the pure strategies. The paper generalizes a former model proposed by the authors for the case of one recycling and one production batch to the case of arbitrary batch numbers.     

Optimizing service-level and relevant cost for a stochastic multi-item cyclic production system

A multi-item make-to-order production system in a stochastic environment is analyzed. Assuming a common cycle production approach, the impact of safety stock, cycle time, demand, processing time and setup time on service-level and total relevant cost (holding, setup and backorder cost) is determined. To illustrate this relationship a trajectory for the service-level with respect to the relevant cost (holding and setup) is presented. Furthermore algorithms to calculate the cycle time which leads to maximum service-level at constant safety stock and to calculate the pair cycle time and safety stock which minimize total relevant cost are introduced.     

Lot sizes in a capacity constrained facility—a simulation study of stationary stochastic demand

This paper considers the scheduling of several different items on a single machine, in literature known as the economic lot scheduling problem, ELSP. One of the characteristics of this problem is that the demand rate is deterministic and constant. However, in a practical situation demand usually varies. In this paper we examine if a deterministic model can be used if demand is stationary stochastic. A dynamic programming approach from Bomberger (Manage. Sci. 12(11) (1966) 778) and a heuristic method from Segerstedt (Int. J. Production Econom. 59(1–3) (1999) 469) are used to calculate lot sizes for four items. The production of these items is simulated with different variations in demand rates. Our conclusion is that a deterministic model of this kind can be used in a practical situation where the demand rate is stationary stochastic, but the models must be complemented by a decision rule; which item to produce and when to produce it. In our tests the heuristic method and the dynamic programming approach perform rather similarly with respect to costs and inventory levels, but the dynamic programming approach results in more backorders when there is small variation in demand rates. This study indicates that the model used for determination of lot sizes is of less importance than the decision rule used for identification of the item to produce and when to produce it.     

Lead time reduction strategies in a single-vendor-single-buyer integrated inventory model with lot size-dependent lead times and stochastic demand

This paper studies alternative methods for reducing lead time and their impact on the safety stock and the expected total costs of a (Q,s) continuous review inventory control system. We focus on a single-vendor-single-buyer integrated inventory model with stochastic demand and variable, lot size-dependent lead time and assume that lead time consists of production and setup and transportation time. As a consequence, lead time may be reduced by crashing setup and transportation time, by increasing the production rate, or by reducing the lot size. We illustrate the benefits of reducing lead time in numerical examples and show that lead time reduction is especially beneficial in case of high demand uncertainty. Further, our studies indicate that a mixture of setup time and production time reduction is appropriate to lower expected total costs.     

Fixed and mobile competition in transition economies

The main aim of this paper is to explore the competition between traditional fixed line and mobile services across Eastern Europe and the Former Soviet Union. Whilst there have been some pioneer studies in the US, empirical evidence for other regions is very limited. Transition countries witnessed important trends in the mobile segment of the market. First, mobile penetration rates have been growing at exponential rates, whereas fixed line penetration rates have at best stagnated. The present analysis is based on empirical evidence based on country level data and case studies, as well as enterprise level data based on major surveys that the EBRD and the World Bank undertook in 2002 across all transition economies. Econometric analysis at the enterprise level shows some interesting results, including evidence of strong network externalities and fixed to mobile substitution effects at the country level.