Dynamic interactive control of inventory in a dual-channel supply chain under stochastic demand: Modelling and empirical studies

Author(s):  
Chuan Zhao ◽  
Luyao Li ◽  
Haoxiong Yang ◽  
Mingke He
2021 ◽  
Vol 2021 ◽  
pp. 1-25
Author(s):  
Ruchi Chauhan ◽  
Varun Kumar ◽  
Tapas Kumar Jana ◽  
Arunava Majumder

With the advancement of technology, many companies provide customization facilities to customers. This facility provides a vast variety to customers which enhances the level of customer satisfaction. This approach helps various technologically advanced companies to increase their profit. In this paper, a dual-channel supply chain model is developed with the aforementioned customization strategy with the target of increasing the profit of the firm. In dual-channel, the core or standard product is provided to the customer through a traditional retail channel, whereas the customized product is made available through the online channel. This article incorporates a modification in the existing dual-channel policy on the number of customers that switch between the offline and online channels. Moreover, a preassigned threshold value is also assumed which signifies the decrease in demand that takes place if the difference between the selling price of offline and online channels crosses a fixed specified threshold value. In addition to that, due to fluctuation and uncertainty of demand, both variability and randomness may occur simultaneously. Thus, the price-sensitive stochastic demand is considered to develop the dual-channel centralized supply chain model with customization. A max-min distribution-free approach is applied to deal with the randomness and variability of demand. The model is analyzed and validated with numerical experiments and graphical analysis. Consequently, the article concluded that it is better to adopt a dual-channel supply chain policy for better profitability than the traditional single-channel supply chain as this firm will be able to provide customized products to customers. Moreover, if the difference between the selling prices of the offline and online channels is greater than the preassigned threshold value, then the shifting of customers takes place depending upon the factor that which channel’s selling is less in comparison to another.


2020 ◽  
Vol 12 (22) ◽  
pp. 9577
Author(s):  
Syed Asif Raza

Corporate social responsibility (CSR) has received much of the attention in supply chain management, in particular the pricing decisions. Most existing models that enable CSR integration into pricing decisions in a supply chain context assume deterministic demand and focus on a single distribution channel. Despite the fact that dual-channel supply chain (DCSC) has received popularity, most pricing decisions models in DCSC assume fixed and deterministic market share distribution between channels, and no demand leakages (cannibalization). This paper addresses these gaps by proposing a CSR enabled DCSC model pricing in which the demand is considered to be stochastic and market share distribution between channels in DCSC is optimally determined using a differentiation price, and the impact of demand leakages is also taken into consideration. Unlike existing studies, which only enable pricing decisions due to deterministic demand consideration, comprehensive DCSC models are proposed that provide joint decisions framework on CSR investment, pricing, and inventories. We have also considered the extension of the demand scenario when the distribution of demand is unknown. The two most common coordination schemes, the centralized (integrated) and the decentralized coordination is explored for the three demand situations: (i) deterministic demand; (ii) stochastic with full information; and (iii) stochastic with partial information. We are able to find analytical (closed-form) solutions for most demand situations. The centralized coordination performed better compared to the decentralized for all demand scenarios. The models are benchmarked when the demand is stochastic with known and unknown distributions, as well as, the case of the deterministic demand. A detailed numerical analysis is also presented in order to study the impact of using the price differentiation for market segmentation, the demand leakage, and partial knowledge on the stochastic demand on the players’ decisions and revenues in the supply chain.


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