Demand Uncertainty

Sales and operations planning (S&OP), despite its importance in balancing demand and supply, faces significant challenges due to system complexity, uncertainty, and conflicting objectives. While previous research has primarily examined the effects of integration, flexibility, and inventory control on cost and customer service level under demand uncertainty, it has often overlooked the simultaneous consideration of plan stability, procurement time uncertainty, and supplier capacity constraints. This study addresses these gaps by developing a multi-objective S&OP simulation–optimization model that jointly considers plan stability objectives and capacity-constrained supply order allocation under both demand and procurement time uncertainty. Computational results from an automotive industry case study show that frozen horizon length has a more significant impact on customer service, delivery time, and plan stability than on total profit. A bi-sourcing policy proved more advantageous than single sourcing even under unlimited capacity and lower unit costs, while moderate procurement lead-time uncertainty outperformed deterministic lead times under long supply intervals. This reveals counterintuitive temporal supply dynamics in which lead-time overlaps and order crossings yield favorable logistics cost trade-offs. The results also indicate that sourcing policies, supply intervals and lead-time uncertainty influence plan stability even when frozen horizon length is fixed. These findings provide manufacturers with insights to balance flexibility and stability in S&OP, while managing multiple uncertainty sources and multi-sourcing strategies in dynamic supply chain environments.

Aujourd'hui, dans un contexte caracterise par une forte concurrence, la chaine d'approvisionnement est consideree comme la cle du succes ou de l'echec de toute entreprise, ce qui a donne lieu a plusieurs etudes et recherches menees dans ce sens.A travers cet article, nous analyserons cette correlation au niveau du tissu industriel marocain a travers les resultats d'une etude quantitative visant a etudier l'impact de la chaine d'approvisionnement, sa conception et son developpement sur la performance de l'entreprise.

A material requirements planning simulator with a two-level bill-of-material is used to study the impact of introducing component commonality into an assemble-to-order environment when demand is subject to random variations, and component procurement orders experience random delays. By using simulated data, our ANOVA results show that component commonality significantly interacts with existence of demand and supply chain uncertainties, and benefits of component commonality are most pronounced when both uncertainties exist.

We consider the design of a two echelon production distribution network with multiple manufacturing plants, customers and a set of candidate distribution centers. The main contribution of the study is to extend the existing literature by incorporating the demand uncertainty of customers within the distribution center location and transportation mode allocation decisions, as well as providing a network design satisfying the both economical and service quality objectives of the decision maker within two levels supply network setting. We formulate the problem as two stage integer recourse problem to find a set of optimal network configuration and assignment of transportation modes and the respective flows in order to minimize total cost and total service time, simultaneously. We develop a stochastic optimization model under demand uncertainty, where the inherent risk is modeled by scenarios. Finally, we propose solution methods for our stochastic optimization problem based on L-shaped algorithm within an ǫ-optimality framework and present numerical results demonstrating the computational effectiveness.

This paper considers dual channel closed loop supply chain with one manufacture and two retailers. A manufacturer combined the offline channel with a direct online channel in product sales. In this research, we inspected the dual channel closed loop supply chain model by notice delivery lead time for the online channel and price discount contracts. We constructed mathematical models with the profit maximization motive which is determined by three decision variables. Furthermore, we determine the optimal solution of the model. We analyze the effects of delivery lead time and price discount contract on the optimal operation. The results of the study show that delivery lead time strongly influences on the optimal profit system and price discount contract perform better than non-contract scenarios.This paper considers dual channel closed loop supply chain with one manufacture and two retailers. A manufacturer combined the offline channel with a direct online channel in product sales. In...

Rewarding customers with own products or services has become an increasingly popular practice across a spectrum of industries such as airlines, hotels, and telecommunication. In these service industries, firms face demand uncertainty and strict short-term capacity constraint. When the market demand is low, firms hold excess capacities that would lead to intense price competition. In this paper we study the adoption and design of reward programs in the context of capacity management. We demonstrate that it is optimal for firms to offer capacity rewards when the market demand varies from one period to the other. By offering the reward programs, firms can effectively reduce available capacities when the market demand is low, and hence credibly show their unwillingness to undersell. Such a commitment can encourage their competitors to set their prices high. When firms provide reward programs, if a firm sets a higher price than the other and sells less today, in the future the firm can b...

Revenue sharing contracts, in which retailers pay a royalty on their sales to their suppliers, are now widely used in video rental retailing. This paper argues that revenue sharing is a valuable instrument in vertically separated industries when there is intrabrand competition among the downstream firms, demand is stochastic or variable, and downstream inventory is chosen before demand is realized. In these environments, the upstream firm would like to simultaneously soften downstream competition and encourage efficient inventory holding. Two-part tariffs are unable to achieve both objectives in the presence of downstream competition. Raising the unit price of the inputs above marginal cost softens retail price competition but distorts retailers' inventory decisions. We show that revenue sharing, combined with a low input price, aligns the incentives in the vertical chain.

If capacity is costly and prices must be set in advance, then firms facing uncertain market demand will not sell all of their output at the same price. Instead firms will offer their output at different prices, with the expectation that lower priced units will be sold more frequently. For large capacity costs, this paper solves the oligopoly problem for price competition under demand uncertainty by expanding the firms strategies to include pure strategy distributions of prices and shows that both intrafirm as well as interfirm price dispersion arise in the unique Nash equilibrium. Furthermore, by comparing three different market structures: perfect competition, oligopoly with symmetric firms, and monopoly, the paper shows first that the Nash equilibrium of the oligopoly model approaches the perfect competition equilibrium as the number of firms approaches infinity, a result that establishes the robustness of the perfect competition model, and second that equilibrium prices are more disperse the more competitive is the market, a result recently documented in an empirical study of airline pricing.

I present a strategic model of competition in price and availability in which demand is uncertain and consumers choose where to shop given firms' observable prices and their expectations of firms' unobservable inventories. In both a single period Cournot model (inventories are chosen first) and a single period Bertrand model (prices are chosen first) I show that firms use higher prices to "signal" higher availability. This creates a floor on equilibrium prices and industry profits regardless of the number of firms. The model is useful in understanding the relationship between price and availability in the video rental industry.

This paper considers a firm's price and inventory policy when it faces uncertain demand that depends on both price and inventory level. The authors extend the classic newsvendor model by assuming that expected utility maximizing consumers choose between visiting the firm and consuming an exogenous outside option. The outside option represents the utility the consumer forgoes when she chooses to visit the firm before knowing whether or not the product will be available. The authors investigate both the case in which the firm's price is exogenous and the case in which price is chosen optimally. The paper makes two contributions. First, the authors show that the firm holds more inventories, provides a higher fill rate, attracts more customers, and earns higher profits when it internalizes the effect of its inventory on demand. Second, the authors show that in the endogenous price case the firm's two-dimensional decision problem can be reduced to two, sequential, single-vari...

Université de Nice-Sophia Antipolis GREDEG-CNRS, France [email protected] This paper analyses the properties of the advanced Opaque booking systems used by online travel agencies in conjunction with their traditional transparent booking system. In section 2 an updated literature review is presented. This review underlines the interest and the specificities of Opaque goods in the Tourism Industry. It also characterises properties of the Name-YourOwn-Price channel introduced by Priceline and the Opaque channel developed by Hotwire. Then, in section 3, the possibility of joint-implementation of more than one opaque booking system by an online intermediary is discussed. Finally, in section 4, intuitions and preliminary results are presented.

Demand forecasts are essential for managing supply chain activities but are difficult to create when collaborative information is absent. Many traditional and advanced forecasting tools are available, but applying them to a large number of customers is not manageable. In our research, we use data mining techniques to identify segments of customers with similar demand behaviors. Historical usage is used to cluster customers with similar demands. Once customer segments are identified, a manageable number of forecasting models can be built to represent the customers within the segments.

The canonical model of a firm selling to heterogeneous, but indistinguishable, consumers implies that the firm should offer multiple products and distort its product quality relative to the efficient level, yet in practice many firms adopt a single product strategy. This tension can be resolved by recognizing that in many instances the firm’s choice of product quality is constrained. We analyze a model of a quality-constrained monopolist’s product line decision that encompasses a variety of important examples of second-degree price discrimination, including intertemporal price discrimination, coupons, advance purchase discounts, versioning of information goods, and damaged goods. We derive necessary and sufficient conditions for price discrimination to be profitable that generalize existing results in the literature. Specifically, we show that when a continuum of product qualities are feasible, price discrimination is profitable if and only if the ratio of the marginal social value ...

This paper argues that revenue sharing is a valuable instrument in vertically-separated industries when there is intrabrand competition among the downstream firms, demand is stochastic or variable, and downstream inventory is chosen before demand is ...

This study develops a comprehensive system dynamics model for retail operations that includes the operations in marketing, merchandising, and store execution of supply chain (SC) management. The simulation is built based on a Delphi study and shows that benefits in marketing and merchandising operations are as significant as those in SC.

We develop an option model to quantify and price a flexible supply contract, by which the buyer (a manufacturer), in addition to a committed order quantity, can purchase option contracts and decide whether or not to exercise them after demand is realized. We consider both call and put options, which generalize several widely practiced contracting schemes such as capacity reservation and buy-back/return policies. We focus on deriving (a) the optimal order decision of the buyer, in terms of both the committed order quantity and the number of option contracts; and (b) the optimal pricing decision of the seller (which supplies raw materials or components to the manufacturer), in terms of both the option price and the exercise price. We show that the option contracts shift part of the buyer's risk due to demand uncertainty to the supplier; and the supplier, in turn, is compensated by the additional revenue obtained from the options. We also show that a better alternative to the two parties' individual optimization is for them to negotiate a mechanism to share the profit improvement over the no-flexibility contract. Indeed, this profit sharing may achieve channel coordination.

I n this article, we study the newsvendor problem with endogenous setting of price and quoted lead-time. This problem can be observed in situations where a firm orders semi-finished product prior to the selling season and customizes the product in response to customer orders during the selling season. The total demand during the selling season and the lead-time required for customization are uncertain. The demand for the product depends not only on the selling price but also on the quoted lead-time. To set the quoted lead-time, the firm has to carefully balance the benefit of increasing demand as the quoted lead-time is reduced against the cost of increased tardiness. Our model enables the firm to determine the optimal selling price, quoted lead-time, and order quantity simultaneously, and provides a new set of insights to managers.

This paper investigates the relationship between market conditions and the value and use of sourcing flexibility for service processes. We develop and analyze a series of models, and we derive expressions for the optimal switching decision, the value of the option to outsource, the value of the option to backsource, and the probability and timing of switches between the alternative sources. One contribution is the models and associated derivations, which are largely new to the literature and may serve as a tool to support service sourcing plans and decisions. The second contribution is a series of results with managerial implications: (1) The probability of outsourcing is generally increasing in volatility for high-skill process and decreasing in volatility for low-skill processes. Earlier work has found that the hysteresis band is increasing in volatility, which is interpreted as an indicator of increasing organizational inertia. We also find that the hysteresis band is increasing in volatility, but interestingly for the case of high-skill processes, organizational inertia tends to be decreasing in volatility. (2) The option to backsource is generally more valuable for high-skill processes than for low-skill processes. This result suggests that investments to make it easier to backsource should have a higher priority for high-skill processes. (3) The value of the option to backsource a high-skill service process can be decreasing in volatility. The result suggests that a rather nuanced consideration of volatility is in order when considering investments in the flexibility to backsource a high-skill process.

This paper analyzes how learning behaviors can substantially modify the outcome of competition in an oligopolistic industry facing demand uncertainty. We consider the case of a symmetric duopoly game where firms have imperfect information about market demand and learn through observing the volume of their sales. The main body of the paper consists in showing how market experimentation can explain the existence of price dispersion in an oligopolistic industry. We study this phenomenon and its dynamic evolution in the context of a Hotelling duopoly model; we then extend the analysis to general demand functions, to N-firm oligopolies, to asymmetric duopolies. We evaluate the social cost of price-experimentation by oligopolistic firms and we emphasize several implications of the public good aspect of information about market demand. We then conclude by a few comments on what happens when the value of information in the oligopolistic industry is negative.

A technique is proposed for estimating the probability distribution of total network travel time, in the light of normal day-to-day variations in the travel demand matrix over a road traffic network. A solution method is proposed, based on a single run of a standard traffic assignment model, which operates in two stages. In stage one, moments of the total travel time distribution are computed by an analytic method, based on the multivariate moments of the link flow vector. In stage two, a flexible family of density functions is fitted to these moments. It is discussed how the resulting distribution may in practice be used to characterise unreliability. Illustrative numerical tests are reported on a simple network, where the method is seen to provide a means for identifying sensitive or vulnerable links, and for examining the impact on network reliability of changes to link capacities. Computational considerations for large networks, and directions for further research, are discussed.

The cost of building a hydrogen (H 2 ) infrastructure is often said to be a major obstacle to the introduction of hydrogen vehicles to the current mix of road vehicles. But there are a number of ways of producing and distributing hydrogen, each with different associated costs. In addition, changes in key factors, such as technology development and level of demand for hydrogen, will affect costs. This paper looks at factors affecting the costs of hydrogen infrastructure over time for a small, but growing demand from fleet vehicles (e.g. buses or other vehicles) in London. The effects of changes in three key factors, namely H 2 demand, technology development, and energy prices (electricity and gas) over time, on the unit of cost of hydrogen are analysed. The analysis and results discussed here have been taken from a PhD project in progress at Imperial College. It is found that the level of demand (for H 2 ) and its rate of growth is the main factor affecting the unit cost of hydrogen over time, as well as the relative costs of the various production-delivery options.

Uncertain parameters appear in many optimization problems raised by real-world applications. To handle such problems, several approaches to model uncertainty are available, such as stochastic programming and robust optimization. This study is focused on robust optimization, in particular, the criteria to select and determine a robust solution. We provide an overview on robust optimization criteria and introduce two new classifications criteria for measuring the robustness of both scenarios and solutions. They can be used independently or coupled with classical robust optimization criteria and could work as a complementary tool for intensification in local searches.

An optimization model is proposed to redesign the supply chain of spare part delivery under demand uncertainty in a specified planning horizon. Long term decisions involve new installations, expansions and elimination of warehouses handling multiple products. It is considered which warehouses should be used as repair work-shops to store, repair and deliver used units to customers. Tactical planning includes deciding inventory, and the connection links between the supply chain nodes. At the tactical level it is determined how demand of failing units is satisfied, and whether to use new or used parts. The uncertain demand is addressed by defining the optimal amount of safety stock that guarantees certain service level at a customer plant. Due to the nonlinear nature of the original formulation, a piece-wise linearization approach is applied to obtain a tight lower bound of the optimal solution. The formulation is applied to the supply chain of electric motors.

This paper evaluates the simultaneous determination of price and inventory replenishment when a firm faces demand from distinct market segments. A firm utilizes fences, such as advance or nonrefundable payment, to maintain separation of its market segments; however, fences are imperfect and allow a degree of demand leakage from the higher-priced to the lower-priced market segment. We investigate the optimal structure of joint price and inventory decisions with fencing, and demonstrate that more segments is not necessarily better, especially when demand uncertainty is high in the presence of lost sales. We also show the impact of imperfect fences on the firm's profitability, and evaluate how fencing costs affect the optimal fencing decision.

Private participation in the construction and operation of road infrastructure ia a way to deal with tight budget constraints and increasing demand for additional road capacity. Fixed term concessions has been the standard contract between the the public sector and private operators with poor results derived mainly from demand uncertainty. This paper analyzed different concession contracts in the context of

Road pricing has been defended by economists as a useful instrument to internalize the costs that road users impose upon other users and the rest of society, with the aim of allocating scarce space and to reduce congestion to an efficient level. More recently, private participation in the construction, maintenance and operation of road infrastructure has been growing all over the world to face the challenge of tight budget constraints and increasing demand for additional road capacity. Fixed term concessions have been the standard contract between the public sector and private operators. Demand uncertainty and fixed term contracts have made impossible to fulfill the concession agreement in many cases, and contract renegotiation has been used to restore financial equilibrium. This has some undesirable economic consequences: selecting the most efficient concessionaire is not longer guaranteed and prices lose their role as signals for allocative efficiency. This paper addresses the problem of giving that role back to pricing, analyzing the possibility of achieving efficient pricing and cost recovery without contract renegotiation.

The information and communication technologies (ICT) sectors are in a process of technological convergence. Determinant factors in this process are the liberalisation of the telecommunications markets and technological change. Many firms are engaged in a process of mergers and alliances to position themselves in this new framework. Technological and demand uncertainties are very important. Our objective in this paper is to study the economic determinants of the strategies of the firms. With this aim, we review some key technological and demand aspects. We shed some light on the strategic motivations of the firms by establishing a parallel with the evolution of the retailing sector.

Vendor Managed Inventory (VMI) is currently seen as a short-term replenishment pull system. Moreover, VMI is usually synonymous with a distribution context and stable demand. However, industrial partners are faced with uncertainty in the context of a B to B relationship. Thus, an adaptation of the actors' planning processes is needed and the question is posed of the interest of VMI in a context of uncertain demand. The purpose of this paper is firstly to analyze the link between VMI and pull logic. Secondly, we explore the extension of VMI notions to the relationship between industrial partners and we confront VMI with uncertain demand in terms of trend, vision of the trend and variability in order to verify the usual stable demand assumption. We also present an integration of VMI into a simulation tool called LogiRisk that we have developed for the evaluation of risks of in supply chain collaboration policies, and a small case study.