Selling Price Dependent Demand Research Articles

Manufacturer-Retailer Integrated System for Multi-Item Considering Two-Level Trade Credit, Volume Flexible, and Selling Price Dependent Demand

Manufacturer-Retailer Integrated System for Multi-Item Considering Two-Level Trade Credit, Volume Flexible, and Selling Price Dependent Demand

Benefits of Preservation, Green and Quality Improvement Investment for Waste Management in Sustainable Supply Chain under Fuzzy Learning and Inflation

In the modern world, waste management, incorporating the quality of the products, energy consumption, and environmental concern have become significant challenges for supply chain managers. Also, smart devices are essential for daily life in the current socioeconomic environment, and customers primarily contemplate a smart product’s price and energy usage before purchasing that. In this situation, to maintain a balance between the selling price, energy consumption, and carbon emission from supply chain operations becomes necessary. So this study develops a twoechelon sustainable inventory model for deteriorating items with an imperfect production process under energy consumption and selling price dependent demand. The producer makes a rework process and quality improvement investment to mitigate defective products and enhance the quality of the products. The present model develops under the influence of inflation. Also, preservation and green technologies are used to mitigate the rate of deterioration and carbon emission, respectively. Firstly, the model is created in a crisp sense, and then expanded into a fuzzy learning model to examine the impact of the learning effect in an imprecise environment. A numerical analysis is performed to validate the proposed model, and the cost function’s convexity is shown graphically using mathematica software. The result of the proposed model provides significant insights to decision-makers on how to efficiently reduce waste while still minimizing the total cost of the system by investing in high efficiency preservation, quality improvement and green techniques. Also, due to learning in fuzziness, the fuzzy learning model gives the lowest total cost, followed by the fuzzy and crisp model. Finally, for various parameters, a sensitivity analysis is performed to gather valuable observations and management insights.

Consumer response to adjustable price and shelf-life of fresh food products under effective preservation policy

Food products deteriorate with time, that affects their freshness and demand. Several preservation policies have been suggested in literature for controlling the deterioration. This research work proposes a supply chain model comprising of a manufacturer and a retailer for deteriorating products with controllable rates of deterioration by improving product’s lifetime (freshness) through preservation in form of storage conditions and delayed ripening agents (preservatives). Customers’ purchasing power controls the purchase quantity; thereby allowing them to buy more products for lower prices and vice versa. This observation is incorporated in this study by considering selling price dependent demand for fresh food items. The proposed model considers a variable (lifetime dependent) component of selling price to integrate consumers’ behavior of buying fresher products for higher prices. The proposed supply chain is presented as a nonlinear mathematical model which is solved by using analytical optimization methods and numerical approaches. Considering the given assumptions, this study explores optimal decision-making for selling price, investment in preservation technology (PT), and cycle time for optimizing product’s freshness, deterioration rate, and demand to maximize the total supply chain profit. The results of the numerical experiments reveal the benefits of the proposed policies by exhibiting significant improvements in product’s freshness, deterioration rate, demand, and profitability. A nexus of the product’s freshness, selling price, and demand is investigated which suggests keeping the total selling price unchanged while improving the demand by increasing freshness through the proposed preservation policy. Some managerial insights are provided for decision-making within food chains.

Fuzzy Inventory Model under Selling Price Dependent Demand and Variable Deterioration with Fully Backlogged Shortages

Fuzzy Inventory Model under Selling Price Dependent Demand and Variable Deterioration with Fully Backlogged Shortages

Interval valued inventory model for deterioration, carbon emissions and selling price dependent demand considering buy now and pay later facility

Uncertainty refers to a lack of precise knowledge or information about a particular event, situation, or outcome. It is an inherent characteristic of many real-world phenomena and is often associated with the presence of risk or ambiguity. Uncertainty can arise due to various factors, such as incomplete information, unpredictability, complexity, or variability of a system or process. In many cases, uncertainty can lead to difficulties in decision-making and pose challenges in planning, forecasting, and managing risks. There are different types of uncertainty, including epistemic uncertainty, which arises from the inherent randomness or variability of a system or process. This study encompasses the inclusion of all inventory parameters as uncertainty parameters, which are expressed in the form of intervals. Furthermore, demand for the product is taken into account in interval form. The conversion of the differential equation into an interval differential equation is carried out in order to account for the variability in demand within a certain interval. The utilisation of the centre-radius technique leads to the derivation of the related optimisation problem under a ‘buy now, pay later’ (BNPL) payment scheme. In order to demonstrate the concept, a numerical case is selected and solved with the MATHEMATICA software and interval order relations. In the end, a comprehensive sensitivity analysis has been conducted to derive insightful conclusions pertaining to this study.

A reverse logistic inventory model with stock and selling price dependent demand under the impact of inflation and learning for non-instantaneous deteriorating products

A reverse logistic inventory model with stock and selling price dependent demand under the impact of inflation and learning for non-instantaneous deteriorating products

A reverse logistic inventory model with stock and selling price dependent demand under the impact of inflation and learning for non-instantaneous deteriorating products

A reverse logistic inventory model with stock and selling price dependent demand under the impact of inflation and learning for non-instantaneous deteriorating products

A study of a lock fuzzy EPQ model with deterioration and stock and unit selling price-dependent demand using preservation technology

A study of a lock fuzzy EPQ model with deterioration and stock and unit selling price-dependent demand using preservation technology

Fuzzy Inventory Model with Variable Production and Selling Price Dependent Demand under Inflation for Deteriorating Items

The main purpose of this paper is to develop an inventory model under fuzzy approach by considering the effect of inflation and time value of money, to determine the optimal time period for inventory cycle and minimum total average costs. The model is integrated production inventory model developed where; the Demand has a direct linear impact on production rate. The model can be divided into four stages. In the first two stages with original production rate and subsequent change in production rate, inventory level rises. Third stage is time after the accumulation of inventory and before the deterioration starts, where demand which selling price dependent is depreciating the inventory level, while in the fourth stage deterioration occurs, which is considered to follow two parameter Weibull distribution. The back-order is not considered. Hexagonal fuzzy numbers are used to derive optimum solution and defuzzification by graded mean integration representation method. A numerical example is given to demonstrate the applicability of the purposed model and sensitivity analysis is carried out to reveal the impact of change in parameter values.

Online-Retail Supply Chain Optimization with Credit Period and Selling Price-Dependent Demand

Credit payment strategies have been implemented widely in the online retail industry. This work studies an online-retail supply chain involving credit period and selling price-dependent demands. The participants of the supply chain form a Stackelberg game where the supplier as a follower sells products to the customers through an online platform provider, who as a leader provides a credit period to customers and charges the supplier based on the quantity of goods sold. We study and compare the supply chains when the online platform provider adopts the cash payment and credit payment strategies, respectively, to investigate the effects of the credit period, the selling price and the default risk on supply chain system performance. We also investigate these supply chains under both the centralized and decentralized settings and provide an example to illustrate a simple allocation mechanism to coordinate the decentralized supply chain. Finally, an extension of the supply chain with credit payment is given.

Replenishment Model with Entropic Order Quantity for Deteriorating Items under Inflation

The purpose of the current paper is to determine an optimal order quantity so as to minimize the total cost of the inventory system of a business enterprise. The model is developed for deteriorating items with stock and selling price dependent demand under inflation without permitting shortage. Optimal solution is achieved by cost minimization strategy considering replenishment cost, purchase cost, holding cost and deterioration cost with a special approach to entropy cost for bulk size purchasing units. The effectiveness of the proposed model has been avowed through empirical investigation. Sensitivity analysis has been accomplished to deduce managerial insights. Findings suggest that an increased inflationary effect results in increment in the system total cost. The paper can be extended by allowing shortage. The model can be utilized in the business firms dealing with bulk purchasing units of electric equipments, semiconductor devices, photographic films and many more.

A Completely Backlogged Two-Warehouse Inventory Model for Non-Instantaneous Deteriorating Items with Time and Selling Price Dependent Demand

A Completely Backlogged Two-Warehouse Inventory Model for Non-Instantaneous Deteriorating Items with Time and Selling Price Dependent Demand

An EOQ Model of Selling-Price-Dependent Demand for Non-Instantaneous Deteriorating Items during the Pandemic COVID-19

A pricing factor plays a dominant role in consumer behavior in most countries affected by the COVID19 pandemic. People have lost their job while others renegotiated for low-paying jobs during this pandemic. Thus, this article aims to develop a viable model to consider various aspects of the COVID19 pandemic. Here, we develop an optimal ordering quantity inventory model of deteriorating items, which are still in demand depending upon the selling price of the product. The items are assumed to be non-instantaneous deteriorating. The shortage is allowed in lead time and is partially backlogged. A solution procedure is presented to determine an optimal cycle, order quantity, and total average cost. A realistic numerical example is given to validate the proposed model by changing different systems of parameters, where sensitivity analysis has been carried out. The effectiveness of the system has been observed through graphical representation. HIGHLIGHTS The study considers the inventory model for non-instantaneous deteriorating items. Selling price dependent demand is incorporated. The shortage is allowed in lead time and is partially backlogged. Theoretical results have been formed to characterize the optimal solutions. The effect of key parameters is studies rigorously. GRAPHICAL ABSTRACT

Impact of Energy and Carbon Emission of a Supply Chain Management with Two-Level Trade-Credit Policy

Supply chain management aims to integrate environmental thinking with efficient energy consumption into supply chain management. It includes a flexible manufacturing process, more product delivery to customers, optimum energy consumption, and reduced waste. The manufacturing process can be made more flexible through volume agility. In this scenario, production cannot be constant, and with the concept of volume agility, production is taken as a decision variable under the effect of optimum energy consumption. Considering a two-echelon supply chain, we consider a producer and supplier with two-level-trade-credit policies (TLTCP) with the optimum consumption. To reduce the integrated total inventory cost, we believe that demand is a function of the credit period and selling price. The cost function is analyzed, either with the credit period dependent demand rate or with the selling price dependent demand rate through the numerical examples under energy costs. Energy and carbon emission costs are introduced in setup/ordering cost, holding cost, and item cost for producer and supplier. The effect of inflation on the total cost cannot be ignored; this model is being developed for deteriorating items with the simultaneous impact of volume agility, energy, carbon emission cost, and two-level-trade-credit policies with inflation. This supply chain model was solved analytically and obtained the optimum decision variables in a quasi-closed form solution. An illustrative theorem is being utilized to analyze the optimum result for all the decision parameters. The convexity of the objective function is being obtained analytically as well as graphically. Finally, numerical examples and sensitivity analysis are employed to illustrate the present study and with managerial insights.

Trade Credit Production Policy with Weibull Deterioration Rate and Selling Price Dependent Demand

Trade Credit Production Policy with Weibull Deterioration Rate and Selling Price Dependent Demand

The second purchase decision under selling price-sensitive stochastic demand and purchasing price uncertainty

It is quite common for a retailer to stock a specific quantity of a product more than once during a certain time period and then sell the product to the customers during the selling season. The retailer also has the option to make a second purchase, as long as there is a potential profit increase on account of the purchase. Due to the stochastic spot market purchasing price and the selling price dependent random demand, the retailer needs to determine whether a second purchase is necessary and if so what are the corresponding order time, quantity, and selling price in order to maximise the expected profit. In this paper, we develop a reality-adaptable solution algorithm to simplify the solution procedure. We also run simulations to analyse the inventory decisions, and to compute the profits when a second purchase is possible.

An ordering policy for deteriorating items with price-dependent iso-elastic demand under permissible delay in payments and price inflation

ABSTRACTThis paper considers the problem of dynamic decision-making for an inventory model for deteriorating items under price inflation and permissible delay in payment. In this paper, we adopt an iso-elastic and selling price dependent demand function to model the finite time horizon inventory for deteriorating items. The stocks deteriorate physically at a constant fraction of the on-hand inventory. The objective of this paper is to determine the optimal retail price, number of replenishments, and the cycle time under two different credit periods so that the net profit is maximized. We discuss the optimization properties and develop an algorithm for solving the problem based on dynamic programming techniques. Numerical examples are presented to illustrate the validity of the optimal control policy, and sensitivity analysis on major parameters is performed to provide more managerial insights into deteriorating items.

An EPQ model with stock and selling price dependent demand and variable production rate in interval environment

The motto of this paper is to develop a production inventory model in real life situation. In reality, demand of a certain product becomes highly effected by on-hand stock level in stores and the selling price of the product. In the proposed model, demand of the product is dependent on these two vital deceive factors. In real life production systems, always there are some defective products which requires reworking in order to make them useful. The possibility of producing some defective items in regular production process and their reworking has been taken into account in the model. In case of inventories of highly demandable products, it is observed that production rate is proportional to demand. The situation also arises in case of launching a new product or in a multi-stage production system. In this model, production rate is a variable and it varies with the demand rate. Shortages are allowed and it is backlogged fully. Based on these assumptions, several researchers worked on but they considered that the associated inventory cost parameters are fixed real numbers. However, these are not fixed in reality and may vary time to time depending upon some scenario. Main objective of the paper is to develop a production inventory model under those assumptions considering various cost parameters as interval numbers. As a result the corresponding optimization problem is also interval valued. Quantum behaved particle swarm optimization technique has been applied to find the maximum profit in a single cycle. Numerical example and sensitivity analysis are given to illustrate the proposed inventory model.

An entropic order quantity inventory model for quality assessment considering price sensitive demand

In today’s technology-driven world, despite of efficient planning of manufacturing system and development of refined production technologies and control systems; the items produced in a manufacturing system may have some fraction of defectives. Thus inspection of a lot of the items is essential to differentiate perfect and imperfect products. Every business sector has some hidden costs involved in additional managerial cost which are also imperative to calculate for smooth running of the business sector. This work considers an entropic order quantity model with selling price dependent demand and screening to separate imperfect quality products. We find an important observation about effect of entropy cost on the maximization of profit which states that the entropy cost has similar behavior as the selling price of the product. Our findings enlighten the insights of the entropic order inventory model and enrich the advancement of the literature of inventory model. Finally, a hypothetical numerical example is set to validate the model and sensitivity analysis has also been performed to study the impact of various parameters on the optimal solution.

Selling Price Dependent Demand with Allowable Shortages Model Under Partially Backlogged—Deteriorating Items

In this paper an inventory model for items with linear deterioration rate is studied. Demand depends upon the selling price of the commodity i.e. if selling price increases, the market demand decreases and vice versa. Shortages allowed and partially backlogged. There is neither repair nor replacement of deteriorated units occurring during the cycle. The ordering cost, purchasing cost, deteriorating cost, holding cost and the lost sale cost are considered in the inventory management. The model is solved analytically by minimizing the total inventory cost. Finally results are analyzed and demonstrated with illustrative numerical example. Sensitivity analysis is carried out to study the changing of different system parameters of this model.