Production/Inventory Policies for a Two-Echelon System with Credit Period Incentives

Trade credit is a crucial source of capital particularly for small businesses with limited financing opportunities. Inventory models considering trade credit financing have been widely studied. However, while there is extensive research on the single-vendor single-buyer inventory model allowing delays in payments, the systems where the vendor supplies to more than one buyer have received less attention. In this paper, we analyze a two-echelon inventory system where a single vendor supplies an item to two buyers who face a constant deterministic demand. The vendor produces the items at a finite rate and offers the buyers a delay payment period. That is, the buyers can delay the payment for the purchased items until the end of the credit period. Therefore, during such a period, the buyers sell the items and use the sales revenue to earn interest. At the end of the credit period, the buyers should pay the purchasing cost to the vendor for which external funding may be necessary. It is widely accepted that, in general, centralized policies reduce the total cost of the supply chain. Therefore, we first deal with an integrated model assuming that the vendor and the buyers make decisions jointly. However, in some cases, the buyers are not willing to collaborate, and the management of the supply chain has to be carried out in a decentralized manner. Hence, we also address the problem under a non-cooperative setting. Numerical examples are presented to illustrate both models. Additionally, we perform a computational experiment to compare both strategies, and a sensitivity analysis of the parameters is also carried out. From the results, we derived that, in general, it was more profitable to follow the integrated policy excepting when the replenishment costs for the buyers were high. Finally, in order to validate the computational results, a statistical analysis is performed.

Effect of Carbon Emission and Shelf-Life on Random Emission and Random Price Dependent Demand of a Perishable Product in Interval Environment

An inventory of suppliers dealing with supply of raw materials from the natural resources like sugarcane, beetroot, vegetable scraps etc. need to choose the product for supply to the production industries with a great consciousness due to their finite shelf-life and carbon emission property. A product with small shelf-life and carrying the burden of carbon tax need to be sold quickly so that overall profit earn can be maximize in such a situation. Further the situation deteriorates when the selling price of a product is affected by the carbon emission and its absolute value reduces with time. There we need a formal mathematical design that can include all these issues of price and carbon tax so that the supplier can select the best product for sale. In this paper we develop and inventory model to investigate the earnings made by the supplier, selling the product with price- and stock- dependent demand and study the effect of carbon emission and shelf-life. Further we obtain the optimal preservation cost and green investment to reduce the deterioration and carbon emission. We study the model under different cases; deterministic demand, probabilistic demand with random emission and probabilistic demand with random price. We perform the sensitivity analysis.

Single vendor-buyer model with deterministic demand, stochastic lead time and multi-quality degradation

This report examines the supply chain strategies for a specific perishable product, or fresh produce and uses green beans as an example. The quality of the products which are in direct correlation with the value of the product are put into the supply chain model, this type of model is also known as “cold chain”. This report in addition to recent researches in cold chain, looks into multi aspect quality degradation and a stochastic lead time from warehouse to retailer. This model developed creates greater insight into the supply chain strategies of such products.

Single vendor-buyer model with deterministic demand, stochastic lead time and multi-quality degradation

This report examines the supply chain strategies for a specific perishable product, or fresh produce and uses green beans as an example. The quality of the products which are in direct correlation with the value of the product are put into the supply chain model, this type of model is also known as “cold chain”. This report in addition to recent researches in cold chain, looks into multi aspect quality degradation and a stochastic lead time from warehouse to retailer. This model developed creates greater insight into the supply chain strategies of such products.

Pricing and composition of multiple vertically differentiated bundles considering demand uncertainty1

The aim of this paper is to investigate a profit-maximization firm how to determine the composition and prices of multiple bundles. Bundles are sets of components that must meet some technical constraints; furthermore, customers differ in their quality valuations and choose the bundle that maximizes their utility. A mixed integer non-linear program is proposed to solve this problem. First, a two-step approach is employed to obtain the firm’s optimal decision. The result indicates that when the firm faces deterministic demand, the optimal set of bundles it offers is independent of the distribution of customer valuations and does not contain any dominated bundle. In addition, dominated components cannot be used to construct the optimal bundles. Second, the impact of demand uncertainty on the firm’s performance is explored. The results suggest that disregarding the demand risk may result in broader assortment and suboptimal prices. Finally, numerical experiments and sensitive analysis are conducted to provide managerial insights for the pricing and composition of multiple bundles.

Price Differentiation and Inventory Decisions in a Socially Responsible Dual-Channel Supply Chain with Partial Information Stochastic Demand and Cannibalization

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.

Multi-Objective Inventory Model with Lead-Time and Defective Items

Inventory problem are generally classified under decision making problem where lead time plays an important role in performance and services to customers during supply and placement of order of an item orders can be placed in shorter lead time with higher price or in longer lead time with lower cost. In this paper we have formulated multi-objective inventory model with one objective of minimizing the total inventory cost and other objective of maintaining the quality of the product by discarding the defective items. The model involved the deterministic demand, lead time dependent lead time cost, holding cost, ordering cost and inspection cost for inspecting defective items. The techniques of priority goal programming and genetic algorithm are applied and the results are compared. The sensitivity analysis is explained due to restriction in cost parameter. The model is finally illustrated with a numerical example.