A Bargaining Framework in Supply Chains: The Assembly Problem

Nagarajan, Mahesh; Bassok, Yehuda

doi:10.1287/mnsc.1080.0880

Cited by 240 publications

(132 citation statements)

References 37 publications

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“…Several papers study coordination and competition in supply chains with multiple suppliers: Bernstein and DeCroix (2004); Wang and Gerchak (2003);and Nagarajan and Bassok (2003). In these papers limited capacity leads to demand truncation rather than slower delivery times.…”

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confidence: 99%

Obtaining Fast Service in a Queueing System via Performance-Based Allocation of Demand

2007

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Any buyer that depends on suppliers for the delivery of a service or the production of a make-to-order component should pay close attention to the suppliers' service or delivery lead times. This paper studies a queueing model in which two strategic servers choose their capacities/processing rates and faster service is costly. The buyer allocates demand to the servers based on their performance; the faster a server works, the more demand the server is allocated. The buyer's objective is to minimize the average lead time received from the servers. There are two important attributes to consider in the design of an allocation policy: the degree to which the allocation policy effectively utilizes the servers' capacities and the strength of the incentives the allocation policy provides for the servers to work quickly. Previous research suggests that there exists a tradeoff between efficiency and incentives, i.e., in the choice between two allocation policies a buyer may prefer the less efficient one because it provides stronger incentives. We find considerable variation in the performance of allocation policies: Some intuitively reasonable policies generate essentially no competition among servers to work quickly, whereas others generate too much competition, thereby causing some servers to refuse to work with the buyer. Nevertheless, the trade-off between efficiency and incentives need not exist: It is possible to design an allocation policy that is efficient and also induces the servers to work quickly. We conclude that performance-based allocation can be an effective procurement strategy for a buyer as long as the buyer explicitly accounts for the servers' strategic behavior. AbstractAny buyer that depends on suppliers for the delivery of a service or the production of a make-to-order component should pay close attention to the suppliers' service or delivery lead times. This paper studies a queuing model in which two strategic servers choose their capacities/processing rates and faster service is costly. The buyer allocates demand to the servers based on their performance; the faster a server works, the more demand the server is allocated. The buyer's objective is to minimize the average lead time received from the servers. There are two important attributes to consider in the design of an allocation policy: the degree to which the allocation policy effectively utilizes the servers' capacities and the strength of the incentives the allocation policy provides for the servers to work quickly. Previous research suggests that there exists a tradeoff between efficiency and incentives, i.e., in the choice between two allocation policies a buyer may prefer the less efficient one because it provides stronger incentives. We find considerable variation in the performance of allocation policies: some intuitively reasonable policies generate essentially no competition among servers to work quickly whereas others generate too much competition, thereby causing some servers to refuse to work with the buyer. Nevertheless,...

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confidence: 99%

Obtaining Fast Service in a Queueing System via Performance-Based Allocation of Demand

2007

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“…With three or more players, the outcome is less predictable. Structural rules like "only player 1 can make offers" or "player 1 negotiates with player 2, and subsequently negotiates with player 3" strongly influence the outcome, as Nagarajan and Bassok (2002) demonstrate for an assembly system. For unstructured bargaining among three or more players with common information, cooperative game theory rules out some outcomes, but does not give a sharp prediction.…”

Section: Introductionmentioning

confidence: 89%

Implications of Renegotiation for Optimal Contract Flexibility and Investment

Plambeck

Taylor

2007

Management Science

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I n a stylized model of biopharmaceutical contract manufacturing, this paper shows how the potential for renegotiation influences the optimal structure of supply contracts, investments in innovation and capacity, the way scarce capacity is allocated, and firms' resulting profits. Two buyers contract for capacity with a common manufacturer. Then, the buyers invest in innovation (product development and marketing) and the manufacturer builds capacity. Finally, the firms may renegotiate to allow a buyer facing poor market conditions to purchase less than the contractual commitment and a buyer facing favorable conditions to purchase more. We show that renegotiation can greatly increase the firms' investments and profits, provided that the contracts are designed correctly. Failing to anticipate renegotiation leads to contracts that allow too much flexibility in the buyer's order quantity, and perform poorly relative to contracts designed to anticipate renegotiation. We provide clear conditions under which quantity flexibility contracts with renegotiation coordinate the system. Where quantity flexibility contracts fail, employing tradable options improves performance.

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“…The work of [8] and [9] dealing with cooperative game theory in different contexts, such as the industry of automobile assembly or even the health sector. There is also research concerning the inventory management ( [10], [11], [12] and [13]) or transport ( [14] and [15]).…”

Section: State Of the Artmentioning

confidence: 99%

Model based on Hybridized Game Theory to Optimize Logistics: Case of Blood Supply Chain

Mouatassim¹,

Ahlaqqach²,

Benhra³

et al. 2016

IJCA

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Several researches have been done to optimize different flows in blood supply chain. However, the use of game theory in this sense is rare. The following work focus on the case of Morocco, consisting of 16 Regional Blood Transfusion Centers (RBTC) centralized around a National Blood Transfusion and Hematology Center (NBTHC). An approach based on hybridized game theory is adopted to form core and strongly stable coalitions and optimize as much as possible the transport cost. Firstly, the optimal cost of each coalition of the 33 possible coalitions; that the Director of NBTHC validated; is computed by using a mixed integer linear Programming model (MILP). Then these costs are introduced as data of two other MILP to define which structure minimizes the total cost allocated to each RTBC while maintaining core stability, in the case of the first MILP, and strong equilibrium in the case of the second. The VRPPDTW is also introduced within each coalition in order to optimize the cost of transport more. General TermsMixed integer linear programming, logistics, game theory.

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A Bargaining Framework in Supply Chains: The Assembly Problem

Cited by 240 publications

References 37 publications

Obtaining Fast Service in a Queueing System via Performance-Based Allocation of Demand

Obtaining Fast Service in a Queueing System via Performance-Based Allocation of Demand

Implications of Renegotiation for Optimal Contract Flexibility and Investment

Model based on Hybridized Game Theory to Optimize Logistics: Case of Blood Supply Chain

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