Optimal two-period inventory allocation under multiple service level contracts

Protopappa‐Sieke, Margarita; Sieke, Marcel; Thonemann, Ulrich W.

doi:10.1016/j.ejor.2016.01.013

Cited by 17 publications

(26 citation statements)

References 17 publications

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“…In system (25), the manufacturer first makes the decisions: w t and p 1,t by β 1 and β 2 , and the retailer are followers; his decision p 2,t+1 is directly related to w t+1 and p 1,t+1 as…”

Section: Complexitymentioning

confidence: 99%

“…When the decision parameters are in this range ( 0 < β 1 < ϑ, 0 < β 2 < 1), system (25) will be stable at equilibrium point e ε 2 (w * , p * 1 ). Due to the existence of a large number of parameters in system (25), the stability and bifurcation of the system will be studied intuitively in the next part.…”

Section: Equilibrium Points and Local Stabilitymentioning

confidence: 99%

“…First of all, we analyze the paths of system (25) going into chaos. Figure 21 shows the 2D parameter bifurcation in the (β 1 , β 2 ) plane, where different colors represent different periods of system (25): stable (red), period-2 (yellow), period-3 (green), period-4 (blue), period-5 (cyan), period-6 (claret), chaos (gray), and divergence (white). It can be seen that system (25) can enter into chaos by two ways.…”

Section: Complexity Dynamics With Respect To β Imentioning

confidence: 99%

“…Considering price, service, and discount contracts, Sadjadi et al [24] built a Stackelberg game model to analyze the equilibrium solution and found that service and price discounts can improve the performance of the supply chain. In addition, scholars have explored service competition and service contract issues [25]. When the manufacturer's warranty service competes with the retailer's value-added service, Dan et al [26] found that when the manufacturer improves the level of warranty service, the competition of value-added service would be weakened.…”

Section: Introductionmentioning

confidence: 99%

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The Impact of Service and Channel Integration on the Stability and Complexity of the Supply Chain

Zhou

Chen

2020

Complexity

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This paper constructs a supply chain consisting of a manufacturer and a retailer. Considering channel integration and service cooperation, two dynamic Stackelberg game models are established: one without unit profit allocation M and the other one with unit profit allocation Mε. In two dynamic models, we analyze the influence of relevant parameters on the stability and complexity of the dynamic system and system profit by nonlinear system theory and numerical simulation. We find that the higher adjustment parameters can cause the system to lose stability, showing double period bifurcation or wave-shape chaos. The stable region becomes larger with increase in service value and value of unit profit sharing. Besides, when the system is in chaotic state, we find that the profit of the system will fluctuate or even decline sharply; however, keeping the parameters in a certain range is helpful in maintaining the system stability and is conducive to decision-makers to obtain steady profits. In order to control the chaos phenomenon, the state feedback method is employed to control the chaotic system well. This study provides some valuable significance to supply chain managers in channel integration and service cooperation.

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Section: Complexitymentioning

confidence: 99%

Section: Equilibrium Points and Local Stabilitymentioning

confidence: 99%

Section: Complexity Dynamics With Respect To β Imentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

The Impact of Service and Channel Integration on the Stability and Complexity of the Supply Chain

Zhou

Chen

2020

Complexity

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“…Equilibrium problems regarding retail services and fairness concerns were analyzed. Protopappa-Sieke et al [21] developed the optimal two-period inventory allocation policies under multiple service level contracts in view of the fact that optimal inventory allocation had a significant impact on profits in the retail industry. How a manufacturer responds to a service level contract was analyzed as considering to minimize the expected costs.…”

Section: Introductionmentioning

confidence: 99%

Complexity Dynamic Character Analysis of Retailers Based on the Share of Stochastic Demand and Service

Ma¹,

Di²,

Ren³

2017

Complexity

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Apart from the price fluctuation, the retailers' service level becomes another key factor that affects the market demand. This paper depicts a modified price and demand game model based on the stochastic demand and the retailer's service level which influences the market demand decided by customers' preference, while the market demand is stochastic in this model. We explore how the price adjustment speed affects the stability of the supply chain system with respect to service level and stochastic demand. The dynamic behavior of the system is researched by simulation and the stability domain and the bifurcation phenomenon are shown clearly. The largest Lyapunov exponent and the chaotic attractor are also given to confirm the chaotic characteristic of the system. The simulation results indicate that relatively small price adjustment speed may maintain the system at stable state. With the price adjustment speed gradually increasing, the price system gets unstable and finally becomes chaotic. This chaotic phenomenon will perturb the product market and this phenomenon should be controlled to keep the system stay in the stable region. So the chaos control is done and the chaos can be controlled completely. The conclusion makes significant contribution to the system referring to the price fluctuation based on the service level and stochastic demand.

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Reference‐dependent preferences in flat penalty service‐level contracts

Duhaylongsod

Papier

Öncüler

2023

J of Ops Management

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This paper investigates a supply chain governed by a flat penalty service‐level contract in which missing the target fill rate can lead to costly operational disruption. We focus on near‐miss bias: (1) the preference for near‐miss events, that is, risky production quantities that reach the target but narrowly avoid disruption; and (2) riskier decision‐making due to such preferences. We propose a reference‐dependent behavioral model that explains the near‐miss bias. The findings of a laboratory experiment show that production quantities are evaluated based on realized profits and are below the optimal model prediction. Contracts associated with lower perceived severity, that is, the ratio of flat penalty to wholesale price, result in lower production quantities than those with higher perceived severity, even though the standard model does not predict any effect. A structural estimation analysis indicates that the behavioral model performs better than the standard model in terms of predictive accuracy and goodness of fit. Our analysis provides insights for managers who design supply chain contracts in settings with considerable risk of disruption due to a shortage of critical parts.

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Optimal two-period inventory allocation under multiple service level contracts

Cited by 17 publications

References 17 publications

The Impact of Service and Channel Integration on the Stability and Complexity of the Supply Chain

The Impact of Service and Channel Integration on the Stability and Complexity of the Supply Chain

Complexity Dynamic Character Analysis of Retailers Based on the Share of Stochastic Demand and Service

Reference‐dependent preferences in flat penalty service‐level contracts

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