Coordinating a three-layer supply chain with uncertain demand and random yield

Giri, Bibhas C.; Bardhan, Sudarshan; Maiti, T.

doi:10.1080/00207543.2015.1119324

Cited by 64 publications

(27 citation statements)

References 87 publications

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“…В работах, посвященных проблеме координации цепи поставок [Taylor, 2002;Cachon, Lariviere, 2005;Chiu et al, 2012;Giri, Bardhan, Maiti, 2016;Lackes, Schluter, Siepermann, 2016;Genc, De Giovanni, 2018;Gamchi, Torabi, 2018], рассматриваются следующие типы контрактов с: распределением выручки; обратным выкупом; гибкой ценовой политикой; ретро-бонусом; гибким объемом поставки; а также комбинированные контракты.…”

Section: Introductionunclassified

Supply chain coordination with sales-rebate contract

Berezinets¹,

Zenkevich²,

Nikolchenko³

et al. 2019

Vestnik SPbSU. Management

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manufacturer and retailer. The authors proposed a mathematical formulation of the supply chain coordination problem, formalized the process of the sales-rebate contract conclusion as a threestep game of two players, and formulated the definition of a coordinating contract. The article presents the developed algorithm for constructing a coordinating sales-rebate contract in supply chains, both for the general case and for the case when the contract parameters are additionally restricted. It has been proven that a sales-rebate contract is not coordinating without additional restrictions on the contract parameters. The algorithm proposed is implemented in the case of the Hong Kong supply chain, consisting of a manufacturer and retailer of children's clothes.

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Section: Introductionunclassified

Supply chain coordination with sales-rebate contract

Berezinets¹,

Zenkevich²,

Nikolchenko³

et al. 2019

Vestnik SPbSU. Management

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show abstract

“…Syam et al [14] demonstrated the situations in which a firm can benefit or lose-out from higher sales uncertainty compared with findings from the standard principal-agent models. Giri et al [15] developed a centralised model and decentralised model with uncertain demand and found that buyback contracts failed to coordinate such a supply chain.…”

Section: Introductionmentioning

confidence: 99%

The Entropy Complexity of an Asymmetric Dual-Channel Supply Chain with Probabilistic Selling

Huang

2018

Entropy

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Considering consumers’ attitudes to risks for probabilistic products and probabilistic selling, this paper develops a dynamic Stackelberg game model of the supply chain considering the asymmetric dual-channel structure. Based on entropy theory and dynamic theory, we analyze and simulate the influences of decision variables and parameters on the stability and entropy of asymmetric dual-channel supply chain systems using bifurcation, entropy diagram, the parameter plot basin, attractor, etc. The results show that decision variables and parameters have great impacts on the stability of asymmetric dual-channel supply chains; the supply chain system will enter chaos through flip bifurcation or Neimark–Sacker bifurcation with the increase of the system entropy, and thus the system is more complex and falls into a chaotic state, with its entropy increased. The stability of the system can become robust with the increase of the probability that product a becomes a probabilistic product, and it weakens with the increase of the risk preference of customers for probabilistic products and the relative bargaining power of the retailer. A manufacturer using the direct selling channel may obtain greater profit than one using traditional selling channels. Using the method of parameter adjustment and feedback control, the entropy of the supply chain system will decline, and the supply chain system will fall into a stable state. Therefore, in the actual market of probabilistic selling, the manufacturers and retailers should pay attention to the parameters and adjustment speed of prices and ensure the stability of the game process and the orderliness of the dual-channel supply chain.

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“…Mateen et al [18] discussed how a vendor and multiple retailers interact in a VMI system under stochastic demand. More results in the research of stochastic models can be found in the literature [3,8,9,13,26].…”

Section: Introductionmentioning

confidence: 99%

Bi-Level Programming Approach to Optimal Strategy for Vendor-Managed Inventory Problems Under Random demand

Wan

Liu

2017

ANZIAM J.

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We present an extension of vendor-managed inventory (VMI) problems by considering advertising and pricing policies. Unlike the results available in the literature, the demand is supposed to depend on the retail price and advertising investment policies of the manufacturer and retailers, and is a random variable. Thus, the constructed optimization model for VMI supply chain management is a stochastic bi-level programming problem, where the manufacturer is the upper level decision-maker and the retailers are the lower-level ones. By the expectation method, we first convert the stochastic model into a deterministic mathematical program with complementarity constraints (MPCC). Then, using the partially smoothing technique, the MPCC is transformed into a series of standard smooth optimization subproblems. An algorithm based on gradient information is developed to solve the original model. A sensitivity analysis has been employed to reveal the managerial implications of the constructed model and algorithm: (1) the market parameters of the model generate significant effects on the decision-making of the manufacturer and the retailers, (2) in the VMI mode, much attention should be paid to the holding and shortage costs in the decision-making.

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Coordinating a three-layer supply chain with uncertain demand and random yield

Cited by 64 publications

References 87 publications

Supply chain coordination with sales-rebate contract

Supply chain coordination with sales-rebate contract

The Entropy Complexity of an Asymmetric Dual-Channel Supply Chain with Probabilistic Selling

Bi-Level Programming Approach to Optimal Strategy for Vendor-Managed Inventory Problems Under Random demand

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