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This paper investigated a multistage sustainable production&ndash, inventory model for deteriorating items (i.e., raw materials and finished goods) with price-dependent demand and collaborative carbon reduction technology investment under carbon tax regulation. The model was developed by first defining the total profit of the supply chain members under carbon tax regulation and, second, considering a manufacturer (leader)&ndash, retailer (follower) Stackelberg game. The optimal equilibrium solutions that maximize the manufacturer&rsquo, s and retailer&rsquo, s total profits were determined through the method analysis. An algorithm complemented the model to determine the optimal equilibrium solutions, which were then treated with sensitivity analyses for the major parameters. Based on the numerical analysis, (a) carbon tax policies help reduce carbon emissions for both the manufacturer and retailer, (b) most carbon emissions from supply chain operations negatively impact the total profits of both members, (c) the retailer may increase the optimal equilibrium selling price to respond to an increase in carbon emissions from supply chain operations or carbon tax, and (d) autonomous consumption positively affects both members&rsquo, optimal equilibrium policies and total profits, whereas induced consumption does the opposite. These findings are very managerial and instructive for companies seeking profits and fulfilling environmental responsibility and governments.

The demand for perishable food products is often influenced by the selling price and the age of the items. This is because perishable food products have become commodities from consumers’ point of view, hence, there are very little differences between competing brands. Consequently, factors like price and freshness (or age) become important determinants of consumer demand. This fact has been used to develop several models for managing perishable inventory. However, most of these models were developed from the perspective of a retailer. Today’s increasingly competitive business environment has forced companies to collaborate with fellow supply chain members in an effort to improve profitability and operational efficiency. With this in mind, this article presents a model for managing inventory in a perishable food products supply chain that begins with farming operations where live inventory items are reared and ends with the consumption of processed inventory. The farming and consumption (retail) stages are connected by a processing stage during which live inventory is processed into a consumable form. Consumer demand at the retail stage is a function of the selling price and the freshness of the processed inventory. The farming, processing and retail stages are the three-echelons of the proposed supply chain aimed at maximising the joint supply chain profit. Through a numerical example, the benefits of jointly optimising the inventory replenishment policy (among all three echelons) are quantified by comparing the network performance of a joint optimisation approach (i.e. centralised) to that of an equivalent independent (i.e. decentralised) optimisation policy.

This article develops a sustainable electricity supply chain mathematical model that assumes linear price-dependent customer demands where the price is a decision variable under setup cost and carbon emission. The sustainable electrical supply chain system contained: (a) power generation, (b) transmission substations, (c) distribution substations, and (d) customer. The production rates depend on the demand rate, and demand for electricity by the customers is dependent on the price of electricity where the electrical energy was generated and transmitted through multiple substations to customers. Moreover, we considered that the capacities of transmission rates, power generation, and distances in between two stations are associated with the distribution costs and transmission cost. Here, we used the theory of inventory to develop a new model and suggested a procedure to deduce an optimal solution for this model. Finally, a numerical example and sensitivity analysis are employed to illustrate the present study and with managerial insights.

In order to identify the optimal structure of an electricity power network under the main assumption of a price dependent demand of electrical energy, we presented an optimization model that aims at analyzing the effect of price-dependent demand on the sustainable electrical supply chain system (SESCS). The system included a power generation system, transmission and distribution substations, and many customers. The electrical energy was generated and transmitted through multiple substations to our customers, and the demand for electricity by the customers is dependent on the price of electricity. In the study, we considered the transmission and the distribution costs which depend on the capacities of power generation, transmission rates and distances between stations. We utilized the inventory theory to develop our model and proposed a procedure to derive an optimal solution for this problem. Finally, numerical examples and sensitivity analysis are provided to illustrate our study and consolidate managerial insights.