The long-run implications of the production smoothing model of inventories: An empirical test

This paper provides an empirical test of the long-run implications of the production smoothing model of inventories, the dominant framework for inventory investment research in the past. Intertemporal models of a firm holding inventories of finished goods predict a long-run relationship between inventories, shipments, factor input prices, and the real interest rate which is tested here using cointegration test procedures. These tests provide little support for the predictions of the production smoothing model. In most of the data sets used, test statistics indicate that inventories, shipments, factor input prices, the nominal interest rate, and the inflation rate maintain a long-run equilibrium relationship but parameter estimates of cointegrating vectors are often implausible, typically rejecting hypotheses implied by structural models of the production smoothing motive for holding inventories.     

A generalized lot sizing model for the process cycling problem

Most scheduling/lot sizing models for the single-machine problem assume that aggregate demand equals aggregate production; and that backorders are to be avoided. Where working inventories are low, the scheduler may wish to avoid short production runs and willingly incur some backorder penalties so as to increase the length of production runs and reduce setup costs per unit of time. The model proposed here identifies optimal lot sizes with respect to the backorder/setup cost relationships. Use of the model will result in an optimally balanced inventory even when aggregate inventory levels are changing.     

A cost evaluation method for dynamic line balancing

A procedure is presented for calculating stochastic costs, which include operator (labor) and inventory costs, associated with dynamic line balancing. Dynamic line balancing, unlike the traditional methods of assembly and production line balancing, assigns operators to one or more operations, where each operation has a predetermined processing time and is defined as a group of identical parallel stations. Operator costs and inventory costs are stochastic because they are functions of the assignment process employed in balancing the line, which may vary throughout the balancing period, and the required flow rate. Earlier studies focused on the calculation of the required number of stations and demonstrated why the initial and final inventories at the different operations are balanced.The cost minimization method developed in the article can be used to evaluate and compare the assignment of operators to stations for various assignment heuristics. Operator costs and inventory costs are the components of the cost function. The operator costs are based on the operations to which operators are assigned and are calculated for the entire work week regardless of whether an operator is given only a partial assignment which results in idle time. It is assumed that there is no variation in station speeds, no learning curve effect for operators' performance times, and no limit on the number of operators available for assignment. The costs associated with work-in-process inventories are computed on a “value added” basis. There is no charge for finished goods inventory after the last operation or raw material before the first operation.The conditions which must be examined before using the cost evaluation method are yield, input requirements, operator requirements, scheduling requirements and output requirements. Yield reflects the output of good units at any operation. The input requirement accounts for units discarded or in need of reworking. The operator requirements define the calculation of operator-hours per hour, set the minimum number of operators at an operation, and require that the work is completed. The scheduling requirements ensure that operators are either working or idle at all times, and that no operator is assigned to more than one operation at any time. The calculation of the output reflects the yield, station speed, and work assignments at the last operation on the line.An application of the cost evaluation method is discussed in the final section of the article. Using a simple heuristic to assign operators, the conditions for yield, inputs, operators, scheduling, and output are satisfied. The costs are then calculated for operators and inventories.In conclusion, the cost evaluation method for dynamic balancing enables a manager to compare the costs of assigning operators to work stations. Using this method to calculate the operator and inventory costs, a number of different heuristics for assigning operators in dynamic balancing can be evaluated and compared for various configurations of the production line. The least cost solution procedure then can be applied to a real manufacturing situation with similar characteristics.     

The effect of transaction costs, payment terms and power on the level of raw materials inventories

This paper proposes and tests an explanation for the level of raw materials inventories based on transaction cost economics theory and the role of power in a supply chain. According to this explanation, raw materials inventories are larger the higher a company's transaction costs and the lower its storage-related production and management costs. Factors that affect these costs are the company's vulnerability to opportunism, whether the input becomes more or less costly to store and manage as it moves through the supply chain, payment terms and the company's power in relation to its supplier. This explanation for the level of raw materials inventories was tested on a large sample of customer industries matched to their main supplier industries. Consistent with this theory, the empirical results show that companies hold larger raw materials inventories the more money their suppliers spend on research and development and the less important the customers are to their suppliers. These results are important because they indicate companies must consider a wider range of factors than previously thought necessary when establishing inventory policy.     

Spatial competition with free entry, Chamberlinian tangencies, and social efficiency

Free entry in Löschian spatial competition leads to a tangency between each firm's negatively sloped average revenue and the downsloping portion of average costs—as in Chamberlin's monopolistic competition. It is generally concluded that this equilibrium involves too many inefficiently small firms. However, this conclusion is incorrect. The difference between price and firm marginal production costs in spatial equilibrium is just sufficient to cover the additional marginal cost of output resulting from availability of multiple locations. This Chamberlinian tangency does not imply inefficiency, because it does not include all the social costs and benefits resulting from spatial competition.     

A model of the firm in time and space

We consider a multi-plant monopoly that sells to markets which are geographically separated and which stores product over time via an inventory capability. It is assumed that plant average production cost is U-shaped and that, if the output of a plant's production run were sold to a single market at only one point in time, the plant would operate on the falling portion of its average cost curve. Hence, it is in the interest of the firm to aggregate markets, both spatially and temporally, to lower average production cost. We develop the optimal joint interplant spacing-inventory policy. We also consider the effects changes in freight costs, storage costs, and interest charges have on the firm's optimal policy.     

THE RESURGENCE OF INVENTORY RESEARCH: WHAT HAVE WE LEARNED?

Abstract. Recent empirical and theoretical research on business inventories is surveyed and critically evaluated. While most inventory research has had macroeconomic motivations, we focus on its microtheoretic basis and on potential conflicts between theory and evidence. The paper asks two principal questions. First, how can inventories, which are allegedly used by firms to stabilize production, nonetheless be a destabilizing factor at the macroeconomic level? Second, why, if firms are following the production-smoothing model, is production more variable than sales in many industries? We suggest that the so-called (S,s) model may help answer both questions.     

Random shocks in experimental spot and forward auction markets

Traders face random demand and supply schedules in two experimental auction environments. One is the standard double auction and the other requires sellers to produce and hold inventory before trading. Inventories cannot be held between trading cycles. The endogenous and random cost of inventory disciplines sellers to restrict sales and keep prices relatively high. Anxious buyers may bid up price because total sales cannot exceed inventories. Shocks to the system do not change this behavior except when seller production costs are random. In this treatment, prices converge to the predicted competitive equilibrium. The inventory requirement in all cases increases the earnings of sellers relative to buyers.     

Household production, full consumption and the costs of children

Recent work criticises both the logic and relevance of the theoretical basis of the approach to estimating the costs of raising children adopted in much of the economics literature. This tends to be restricted purely to models in which the household members consume market goods with given household income. The “costs of children” are perceived essentially as market consumption costs. This ignores the fact that an important, possibly preponderant element of child costs takes the form of parental time, which must be diverted from alternative uses such as market work, other household production activities, and leisure, to care for children. The studies also ignore the question of the differential incidence of child costs on adult members of the household. In this paper, we first of all argue that a satisfactory theoretical approach to modelling child costs must simultaneously incorporate an “individualistic” formulation of the household and a formal treatment of household production. We then provide such a model. Using data from a time use survey we estimate specialised versions of the model for families with two children and use the results to derive the intra-family distribution of resources and implied child-rearing costs.     

Improving health care means spending more time with patients and less time with inventory

In most hospitals and medical establishments, about 35 percent of their budgets are spent on supplies and labor to manage the inventories, material, and information flows; typically, these are managed as multiechelon systems. The importance of reducing inventory costs, among others, has become relevant in today's health care management. This research applies just-in-time concepts to health care inventories.     

Production planning and inventories optimization: A backward approach in the convex storage cost case

We study the deterministic optimization problem of a profit-maximizing firm which plans its sales/production schedule. The firm controls both its production and sales rates and knows the revenue associated to a given level of sales, as well as its production and storage costs. The revenue and the production cost are assumed to be respectively concave and convex. In Chazal et al. [Chazal, M., Jouini, E., Tahraoui, R., 2003. Production planning and inventories optimization with a general storage cost function. Nonlinear Analysis 54, 1365–1395], we provide an existence result and derive some necessary conditions of optimality. Here, we further assume that the storage cost is convex. This allows us to relate the optimal planning problem to the study of a backward integro-differential equation, from which we obtain an explicit construction of the optimal plan.     

Optimal inventories for repairable redundant systems with aging components

Complex systems that are required to perform very reliably are often designed to be “fault-tolerant,” so that they can function even though some component parts have failed. Often fault-tolerance is achieved through redundancy, involving the use of extra components. One prevalent redundant component configuration is the m-out-of-n system, where at least m of n identical and independent components must function for the system to function adequately.Often machines containing m-out-of-n systems are scheduled for periodic overhauls, during which all failed components are replaced, in order to renew the machine's reliability. Periodic overhauls are appropriate when repair of component failures as they occur is impossible or very costly. This will often be the case for machines which are sent on “missions” during which they are unavailable for repair. Examples of such machines include computerized control systems on space vehicles, military and commercial aircraft, and submarines.An interesting inventory problem arises when periodic overhauls are scheduled. How many spare parts should be stocked at the maintenance center in order to meet demands? Complex electronic equipment is rarely scrapped when it fails. Instead, it is sent to a repair shop, from which it eventually returns to the maintenance center to be used as a spare. A Markov model of spares availability at such a maintenance center is developed in this article. Steady-state probabilities are used to determine the initial spares inventory that minimizes total shortage cost and inventory holding cost. The optimal initial spares inventory will depend upon many factors, including the values of m and n, component failure rate, repair rate, time between overhauls, and the shortage and holding costs.In a recent paper, Lawrence and Schaefer [4] determined the optimal maintenance center inventories for fault-tolerant repairable systems. They found optimal maintenance center inventories for machines containing several sets of redundant systems under a budget constraint on total inventory investment. This article extends that work in several important ways. First, we relax the assumption that the parts have constant failure rates. In this model, component failure rates increase as the parts age. Second, we determine the optimal preventive maintenance policy, calculating the optimal age at which a part should be replaced even if it has not failed because the probability of subsequent failure has become unacceptably high. Third, we relax the earlier assumption that component repair times are independent, identically distributed random variables. In this article we allow congestion to develop at the repair shop, making repair times longer when there are many items requiring repair. Fourth, we introduce a more efficient solution method, marginal analysis, as an alternative to dynamic programming, which was used in the earlier paper. Fifth, we modify the model in order to deal with an alternative objective of maximizing the job-completion rate.In this article, the notation and assumptions of the earlier model are reviewed. The requisite changes in the model development and solution in order to extend the model are described. Several illustrative examples are included.     

Highway traffic flow and the uneconomic region of production

In this paper highway traffic flow is formulated as a short-run production function in which traffic volume is the output and traffic density is the variable input. Given this formulation, the ‘uneconomic’ region of production is relevant. Often it is the case that traffic density will exceed the point at which traffic volume is at a maximum; i.e., the marginal product of the variable input is negative.     

Inventories and Endogenous Stackelberg Leadership in Two‐Period Cournot Oligopoly

Two‐period Cournot competition between n identical firms producing at constant marginal cost and able to store before selling has pure strategy Nash‐perfect equilibria, in which some firms store to exert endogenously a leadership over rivals. The number of firms storing balances market share gains, obtained by accumulating early the output, with losses in margin resulting from increased sales and higher operation costs. This number and the industry inventories are nonmonotonic in n. Concentration (HHI) and aggregate sales increase due to the strategic use of inventories.     

Pricing competition with inventory considerations in a hazard rate-prone market of durables

This paper addresses Bertrand-type pricing competition between two firms producing partially differentiated durables over a finite planning horizon. The demand for durables, characterized by increasing returns of scale to a price reduction, is led by the hazard rate. While the effect of inventories on pricing of non-durables is widely recognized, the management and marketing literature typically overlooks this effect in regard to horizontally competing firms for durables. In this paper we show that the pricing trajectory of durables may significantly alter when inventory dynamics are accounted for. In particular, the price may hike upwards before dropping; gradually grow; or even stay at the same level over the entire product life while it would only decline if inventories and related costs are disregarded. Furthermore, the well-known, optimal pricing strategy of following the pattern of sales does not necessarily confirm even for symmetric equilibria when the competing firms have either an inventory surplus or shortage.     

Maintenance management: Keeping up with production's changing trends and technologies

Current trends in manufacturing have led to reduced levels of work-in-process inventory and increased levels of automation and machine complexity. These changes have two important implications for maintenance management. First, machine breakdowns not only cause a loss of output from the down machine, but also result in lost production on downstream machines. This occurs because of the elimination of buffer stock between workstations. Second, the gap between the technological expertise of the operators and the technological sophistication of their machines has widened. This gap decreases the ability of operators to make adjustments and minor repairs to their own machines.These two factors cause an increase in maintenance costs associated with machine downtime and maintenance labor. Historically, the proportion of preventive and corrective maintenance has attempted to balance these costs. As buffer stock is reduced and more machines are coupled, the costs of downtime will increase, increasing the need for preventive maintenance and decreasing its cost compared to the cost of lost production.Increases in the use of computer-based planning systems have resulted in the development of computerized preventive maintenance systems that have proven to be successful in planning for maintenance labor and materials. Integrating planning methods with corrective maintenance tasks will help reduce breakdowns, make more efficient use of maintenance craft labor, and provide information for inventory control of maintenance, repair, and operating (MRO) materials.This article examines methods of reducing machine downtime costs, maintenance labor costs, and MRO inventory costs in today's changing production environment. Techniques for reducing these costs are explored in the areas of maintenance planning, maintenance methods improvement, and MRO inventory control.     

Inventory management in the just-in-time age

JIT will change our conventional thinking concerning the management of inventories and streamline our methods for inventory control. Proper selection and implementation of these methods will yield substantial benefits by improving customer service, shortening delivery lead times, and significantly reducing inventory investment. It does not, however, eliminate the need for sound inventory planning.     

Reviewing the literature on non-parametric dynamic efficiency measurement: state-of-the-art

Much of the literature on static efficiency measurement models assumes that the inputs are fully used for producing outputs in the same period, with the result that no time interdependence exists between the input utilization and output realizations for a production unit in consecutive periods. A review of the literature on non-parametric dynamic efficiency models identifies five key factors of the inter-temporal dependence between input and output levels over different periods: (i) production delays; (ii) inventories (inventories of exogenous inputs or inventories of intermediate and final products); (iii) capital or generally quasi-fixed factors (and associated embodied technological change, vintage specific capital); (iv) adjustment costs; and (v) incremental improvement and learning models (disembodied technological change). This paper reviews the literature and finds that the dynamic issues associated with adjustment costs and capital have received considerable attention in the literature, whereas the dynamic issues associated with inventories have received less attention. The paper concludes with suggestions for future research such as relaxing the perfect anticipation/knowledge assumption for future variables, prices, and states. Moreover, Dynamic Network Data Envelopment Analysis has provided a unifying framework for some dynamic factors, but further development of these models is necessary including meaningful applications.     

供应商库存管理在半导体行业的实施

库存管理是影响流水线生产企业成本的重要因素,在实际库存管理过程中,应认真分析企业生产性质和各种库存管理的特点,采取合适的措施,切实做好库存控制工作,满足企业的实际需求。根据半导体行业的实际情况,对具备条件的物料引进供应商库存管理（VMI）,可以获得较好综合效益,切实降低整个供应链的成本,极大调动产业链中企业的积极性。