The Price of Anarchy in Supply Chains: Quantifying the Efficiency of Price-Only Contracts

Perakis, Georgia; Roels, Guillaume

doi:10.1287/mnsc.1060.0656

Cited by 191 publications

(118 citation statements)

References 34 publications

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“…Ferguson (2003) and Ferguson et al (2005) study how firms' preferences for one ordering time over the other are affected by the power structure of the supply chain and the demand uncertainty reduction achieved between the two points in time. Perakis and Roels (2006) establish bounds on the efficiency loss of push and pull contracts in Stackelberg game settings relative to the centralized supply chain. The timing of the retailer's order placement not only affects the inventory ownership but also influences the retailer's effort both to promote demand and to acquire and share demand information.…”

Section: Introductionmentioning

confidence: 99%

Two-Wholesale-Price Contracts: Push, Pull, and Advance-Purchase Discount Contracts

Dong

Zhu

2007

M&SOM

110

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The allocation of inventory ownership affects the inventory availability in a supply chain, which in turn determines the supply chain performance. In this paper, we consider a supplier-retailer supply chain in which the supplier starts production well in advance of the selling season, and the retailer is offered two ordering opportunities at different points in time. An early order is allowed before the supplier's production decision, and a late order is allowed after the completion of production and after observing the demand. When the two wholesale prices change, we illustrate how the inventory decision rights and ownership are shifted and/or shared between the two firms, resulting in push, pull, or advance-purchase discount contracts. We then characterize the complete set of Paretodominant contracts for any given two-wholesale-price contract. We find that Pareto improvement can be achieved when inventory ownership is shifted from individual to shared and sometimes vice versa. In the latter case, push contracts not only are more likely to offer Pareto improvement but also can achieve higher supply chain efficiency than pull contracts. We also identify conditions that enable Pareto improvement by introducing a new ordering opportunity to firms who were bound by a single ordering opportunity without renegotiating the existing wholesale price, and we demonstrate through a numerical study that the adoption of the new ordering opportunity can significantly improve supply chain efficiency. We show that such Pareto improvement is more likely to happen when demand is more volatile.

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Section: Introductionmentioning

confidence: 99%

Two-Wholesale-Price Contracts: Push, Pull, and Advance-Purchase Discount Contracts

Dong

Zhu

2007

M&SOM

110

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“…Note that the optimal solution does not contain supplier backlog, and therefore all occurrences of variables r 2 t can be dropped. The constraints can be derived by substituting both k = 1 and k = 2 into constraints (8)(9)(10)(11)(12), and unifying d We investigate the integrated approach with two different benefit sharing mechanisms. In the first case, each party bears its own costs, and hence, the profits P (3)(4)(5)(6).…”

Section: Computational Modelmentioning

confidence: 99%

“…The potential gain by integrated versus decentralized decision making in supply chains is investigated in [12], where the difference of the induced costs is defined as the price of anarchy. The coordination of supply chains consisting of autonomous enterprises is studied in detail in [2], while a comprehensive taxonomic survey of coordinated buyer-vendor models in a deterministic, time invariant setting is provided in [15].…”

Section: Introductionmentioning

confidence: 99%

Inventory control in supply chains: Alternative approaches to a two-stage lot-sizing problem

Kovács

Egri

Kis

et al. 2013

International Journal of Production Economics

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The principal challenge of inventory control in supply chains is that the interacting autonomous enterprises have to plan their production and logistics under information asymmetry, driven by different, often conflicting objectives. In this paper, four different computational approaches are investigated to cope with this challenge: decomposition, integration, coordination, and bilevel programming. The four approaches are applied to solving the same two-stage economic lot-sizing problem, and compared in computational experiments. The prerequisites of the approaches are analyzed, and it is shown that the profits realized and the costs incurred at the different parties largely depend on the solution approach applied. This research also resulted in a novel coordination mechanism, as well as a new algorithm for the bilevel optimization approach to the investigated lot-sizing problem. A specific goal of this study is to highlight the so far less recognized application potential of the coordination and the bilevel optimization approaches for controlling inventories in a supply chain.

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“…Furthermore, we assume that the supplier and the retailer both act individually rationally and want to minimise their own costs. This partial cooperation typically leads to inefficiencies for the supply chain, see for example Inderfurth et al (2013) and Perakis and Roels (2007). However, we consider the problem from the supplier's point of view, who wants to minimise his own costs, and thus perfect supply chain coordination is not a goal.…”

Section: Introductionmentioning

confidence: 99%

Two-echelon lot-sizing with asymmetric information and continuous type space

Kerkkamp

Heuvel

Wagelmans

2019

Omega

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We analyse a two-echelon discrete lot-sizing problem with a supplier and a retailer under information asymmetry. We assume that all cost parameters are time independent and that the retailer has single-dimensional continuous private information, namely either his setup cost or his holding cost. The supplier uses mechanism design to determine a menu of contracts that minimises his expected costs, where each contract specifies the retailer's procurement plan and a side payment to the retailer. There is no restriction on the number of contracts in the menu.To optimally solve this contracting problem we present a two-stage approach, based on a theoretical analysis. The first stage generates a list of procurement plans that is sufficient to solve the contracting problem to optimality. The second stage optimally assigns these plans to the retailer types and determines all side payments. The result is an optimal menu with finitely many contracts that pools retailer types. We identify cases for which the contracting problem can be solved in polynomial time and provide the corresponding algorithms. Furthermore, our analysis reveals that information asymmetry leads to atypical structures in the plans of the optimal menu, e.g., plans violating the zero-inventory property. Our solution approach and several results are directly applicable to more general problems as well.

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The Price of Anarchy in Supply Chains: Quantifying the Efficiency of Price-Only Contracts

Cited by 191 publications

References 34 publications

Two-Wholesale-Price Contracts: Push, Pull, and Advance-Purchase Discount Contracts

Two-Wholesale-Price Contracts: Push, Pull, and Advance-Purchase Discount Contracts

Inventory control in supply chains: Alternative approaches to a two-stage lot-sizing problem

Two-echelon lot-sizing with asymmetric information and continuous type space

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