Price-sensitive Stochastic Demand Research Articles

The impact of sales effort on a dual-channel dynamical system under a price-sensitive stochastic demand

Sales efforts play a crucial role in dynamic retail management and can have a significant impact on the overall success of a retail business. The primary goal of sales efforts is to generate revenue. By effectively promoting and selling products or services, sales teams can drive sales and increase the company's revenue. Demand of products play a critical role for retailing sector and demand cannot be predicted perfectly in reality. Owing to this situation, a dynamical system with dynamic sales effort and price-sensitive stochastic demand is proposed in this study. A dual-channel (online & offline) is considered in this study to provide the best consumer experience. Contradictory to the existing literature, geometric Brownian motion under a fuzzy environment is utilized to handle the dynamic price situations, which is solved through the Black-Scholes equations. The effect of preseason cost on the optimal results is analyzed. To validate the study, a numerical analysis of the dual-channel retailing system is presented with optimal selling price, sales effort, and profit under stochastic demand. Sales efforts have a profound impact on dynamic retail management. They drive revenue generation, customer acquisition and retention, inform inventory management decisions, provide market insights, contribute to competitive advantage, align with marketing strategies, and enable performance measurement and improvement. From the findings, it is clear that sales effort can provide 0.02% higher profit per cycle in a dual-channel retailing.

A Modified Customization Strategy in a Dual-Channel Supply Chain Model with Price-Sensitive Stochastic Demand and Distribution-Free Approach

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.

Inter-dependent lead-time and ordering cost reduction strategy: a supply chain model with quality control, lead-time dependent backorder and price-sensitive stochastic demand

This research work addresses an inter-dependent reduction strategy of lead time and ordering cost in a two-stage single vendor and single buyer supply chain model with price-sensitive stochastic demand. Buyer’s backorder rate is a variable, as it depends on the variable lead time. Quality improvement is another aspect of this study. The objective of this study is three folds. Firstly, reducing the lead time and ordering cost simultaneously. Secondly, improving the quality of products and third, optimizing order lot size, lead time, process quality parameter, safety factor, ordering cost, lead time crashing cost, backorder rate, and the number of deliveries so that the joint expected total profit becomes maximum. Stackelberg game and Joint decision, both approaches are discussed. Numerical result shows that the Joint decision approach gives better result than the Stackelberg game approach. Sensitivity analysis for Case-III with respect to some key parameters has been carried out.

Supply chain coordination with competing suppliers under price-sensitive stochastic demand

In this paper, we investigate a supply chain where two competing suppliers sell substitutable products through a common retailer who faces price-dependent stochastic demand. The retailer jointly decides the order quantity and the retail price for each product. Unlike most existing research assuming customer homogeneity, we divide the customers into two types: i) the price-sensitive type and ii) the brand-loyalty type, and investigate the issues of supply chain coordination. Our results show that neither buy-back contracts nor the buy-back related hybrid contracts (i.e., the hybrid buy-back and revenue-sharing contract and the hybrid buy-back and sales rebate contract) can achieve the coordination of such a supply chain. Furthermore, under buy-back contracts for the decentralized supply chain, we analyze the retailer's optimal retail price and order quantity when each supplier imposes a minimum order-quantity constraint. Our result shows that there exists a unique optimal decision for the retailer under some mild restrictions.

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.

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

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

Coordinated decision-making on manufacturer’s EPQ-based and buyer’s period review inventory policies with stochastic price-sensitive demand: A credit option approach

Pricing and replenishment decisions are no longer internal issues within organizations and it is of high significance to coordinate such primary decisions from a supply chain (SC) perspective. In this study, for the first time, we develop a new method based on credit option to coordinate production, pricing, and periodic review policy decisions considering a manufacturer-buyer chain under price-sensitive stochastic demand. In the studied SC, the buyer applies a periodic review order-up-to level inventory policy and its decision variables are order-up-to level, selling price and review period. In this case, the manufacturer follows an economic production quantity (EPQ) policy and decides on production multiplier. Firstly, exact algorithms in addition to concavity analysis are addressed to find optimal decisions in centralized and decentralized structures. Afterwards, a credit option mechanism is proposed to obtain mutually acceptable decisions and create a win–win situation for the manufacturer and buyer. Numerical examples and sensitivity analysis along with a real case study are carried out to show the applicability and performance of the credit option contract. The results reveal the capability of the proposed credit option contract in coordinating pricing, production, and periodic review replenishment decisions; thereby encouraging both sides to accept the coordination mechanism. Moreover, the results indicate that the proposed credit option contract can even improve the SC profit more than centralized model under some circumstances.

Coordinating a multi-echelon supply chain under production disruption and price-sensitive stochastic demand

This paper considers a three-echelon supply chain system with one raw-material supplier, one manufacturer and one retailer in which both the manufacturer and the raw-material supplier are exposed to the risk of production disruptions. The market demand is assumed to be uncertain but sensitive to the retail price. The objective is to determine the optimal lot sizes of the supplier and the manufacturer, and the selling price of the retailer when the wholesale prices of the upstream entities are prescribed and the retailer's order quantity is chosen before the actual demand is realized. As the benchmark case, the expected total profit of the centralized channel is maximized. The decentralized supply chain is coordinated under pairwise and spanning revenue sharing mechanisms. Numerical study shows that disruptions have remarkable impact on supply chain decisions.

Impact of inventory cannibalisation on a retailer selling substitutes

The reasons customers substitute, are well understood from an economic perspective. However, its exact impact on retailer's inventory and profit is not, when customers substitute as a result of a shortage. Shortage of one product may lead to demand spillover, due to substitution, resulting in shortages for the second product. We call this inventory cannibalisation. This is a store level, retailer observed phenomenon that is a direct result of customers' willingness to switch between substitutes due to stockout of one product. Many retailers are experiencing stockouts related to substitution, resulting in a significant loss of revenue. We model a retailer's selling two substitutes, facing price-sensitive stochastic demand. Our model incorporates cannibalisation explicitly and generalises the existing literature on inventory substitution. We perform analytical and numerical analysis to study the impact of stockout-based substitution and the related inventory cannibalisation on retailer's decisions. We find that the impact of cannibalisation is felt most acutely by the retailer for products with low degree of substitution.

Random sales price-sensitive stochastic demand

PurposeThis research work introduces an imperfect production system where the demand is assumed to be stochastic and it is influenced by random selling price. The shift time from an “in-control” state to an “out-of-control” state is exponentially distributed. The accumulated inventory contains both perfect and defective items which are all sold with a free repair warranty (FRW) offer. Complete back ordering of shortages are taken into account. The purpose of this paper is to determine the optimal selling price and hence the optimal production lot size such that the expected profit is maximized.Design/methodology/approachThe general model is discussed separately for both types of uniformly distributed selling price-sensitive demand pattern: additive type and multiplicative type. Numerical examples and graphical representations of the optimal solutions are provided to illustrate the models.FindingsThis paper helps the manager to manage future situations and it may be considered as a base work for the researchers to work in this direction.Research limitations/implicationsThe main limitation of this model is to consider a single item for a single channel system. There are many correlated issues that need to be further investigated. The future study in this direction may include the consideration of multi-items, diverse demand pattern with different types of price distributions.Originality/valueIn the production inventory literature, plenty of articles are available considering imperfect production but none of them have considered selling price-sensitive stochastic demand where the sales price is random in character under an FRW offer.

The newsvendor's joint procurement and pricing problem under price-sensitive stochastic demand and purchase price uncertainty

We assume that a newsvendor has a particular time period before the commencement of the selling season to make a one-time “time-flexible” purchase (Li and Kouvelis [19]) from one of the multiple alternative suppliers that differ in their fluctuating price processes, and then sets the price to satisfy the price-sensitive stochastic demand. We develop the joint procurement planning and pricing procedure to maximize the newsvendor's expected profit, and further develop a reality-adaptable solution algorithm to simplify the procedure, which quickly decreases the computational complexity when there exist multiple alternative suppliers and the procurement planning period is long. We analyze how the preseason cost, i.e., the total cost before selling season, affects the firm's optimal order quantity, selling price, and the optimal expected profit, and then compare the joint procurement and pricing decisions (to maximize the expected profit) with separate procurement and pricing decisions, i.e., making procurement decision (to minimize the expected cost) first and then pricing decision (to maximize the expected revenue). Through extensive numerical analysis: (1) We demonstrate that the joint purchasing and selling strategy performs much better than making purchasing and selling decisions separately. (2) We show that the firm's optimal expected profit benefits greatly from increasing the potential supplier base. (3) We study the effect of the key parameters on the purchasing decisions.

Cooperative game analysis of a supply chain with one risk-neutral supplier and two risk-averse retailers

Purpose: This paper considers a two-echelon supply chain composed of one risk-neutral supplier and two risk-averse retailers. The retailers obtain production from the supplier and sell them to the market. Based on the cooperative game theory, the paper studies the appropriate profit allocation of the supply chain when all the players cooperate with each other, where the two retailers face a price-sensitive stochastic demand. The two retailers can either determine their retail prices independently, or decide whether or not to cooperate with each other. Design/methodology/approach: To allocate the system-wide profit among upstream risk-neutral suppliers and two risk-averse downstream retailers, this paper constructed a cooperative game model, considered as the supermodularity of the characteristic function and the Shapley value of the game. Findings and Originality/value: By analyzing the construction’s cooperative game model, the results show that the profit of the whole supply chain is the highest in the grand coalition structure. This paper also shows that the core of our cooperative game is nonempty, and has the supermodularity property. Based on this, we have computed the Shapley value-based profit allocation for the whole supply chain in a fair manner. Originality/value: Although there are a lot of literature examined risk aversion in a supply chain, but they did not consider using cooperative game to study this problem. This the first study is in the context of a supply chain with risk aversion problem.

PRICING AND INVENTORY DECISIONS WITH UNCERTAIN SUPPLY AND STOCHASTIC DEMAND

We consider a retailer, facing uncertain supply and price-sensitive stochastic demand, who has to make stocking and pricing decisions for a given selling period. We also consider the case when the demand is price-sensitive deterministic and provide a unified framework for the model with additive errors. For both scenarios, we look at the case when the price is set before receiving the supply, called simultaneous pricing and the case when the price is set after receiving it, which is called postponed pricing. We develop a procedure for finding the optimal policy for the retailer with general distributions for the supply and the demand. To study the effect of supply uncertainty on expected profit, we conduct sensitivity analysis and develop results for both pricing scenarios and give insights. The results have important implications for a retailer in the supply chain, where a portion of the inventory may be lost due to variety of factors including mishandling and failure to meet quality standards. The findings shed light on the nature and role of prices and their relationship to supply and demand.

Minimizing downside risks for global sourcing under price-sensitive stochastic demand, exchange rate uncertainties, and supplier capacity constraints

In this paper, a methodology for minimizing downside risks in relationship to the supplier base, supplier capacities, purchase-order-quantity, purchase-order-time, and selling-price is presented. Specific purchasing and selling strategies to minimize downside risks when suppliers have limited capacities is offered. Numerical analyses are used to demonstrate the profound impact on risks due to the increases in the potential supplier base, together with the effects of purchasing price trends and the impact factor of selling price to the demand.We assume that the retailer stocks a certain quantity of a single product globally during a certain time period and then sells it to the domestic customers during the selling season. As exchange rate fluctuations are involved in the overseas purchasing and because the demand in the domestic selling is random and negatively impacted by the selling price, the retailer needs to combine uncertainties in both purchasing and selling to determine when an order should be placed, what quantity must be ordered, and what the selling price should be in order to minimize its downside risk, i.e., the possibility of missing target expected profits. We then consider multiple supplier candidates from different countries with limited capacity and determine the corresponding purchasing and selling decisions to minimize downside risks. The study is further extended to allow multiple purchasing at any time during the purchasing period from any supplier candidates.

Research on Service Capacity Coordination Strategy in Product Servitization Supply Chain

This paper introduces a three-echelon product Service-oriented supply chain consisting of specialized service function provider, service integrator and customer. Service integrator purchases service capacity from specialized service function provider and sales the added service to customer facing with a price sensitive stochastic demand market. The purpose of service integrator is to meet expected profit maximization through the optimal service capacity order quantity and price of integrated services. Specialized functions service provider identifies the best service capacity price to maximize the expected profit. Establishing the revenue model and supply chain coordination model in product Service-oriented supply chain based on service capacity. Through the numerical example, we find that service capability has an important influence on product Service-oriented supply chain coordination performance.

Tailored Supply Chain Decision Making Under Price-Sensitive Stochastic Demand and Delivery Uncertainty

In this paper, we study a serial two-echelon supply chain selling a procure-to-stock product in a price-sensitive market. Our analytical modelling framework incorporates optimal pricing and stocking decisions for both echelons in the presence of stochastic demand and random delivery times. We focus on understanding how these decisions for the chain are affected by its management paradigm (centralized or decentralized), and its business characteristics—price sensitivity, demand uncertainty, and delivery time variability. A novel combination of transformations enables us to analyze the framework and determine the unique optimal choices for centralized and wholesale price-based decentralized supply chains. More detailed investigation reveals that, in general, the business characteristics influence both the behavior and the optimal values of the decision variables, while the management paradigm primarily governs the optimal values. We illustrate the significance of these results in terms of how managers should tailor their decisions to align with their business requirements. Subsequently, comparison of the optimal profits between the channel partners and the management paradigms provides implications for decentralization strategy. A decentralized chain is most inefficient for moderately price-sensitive customers and uncertain environments, but is relatively more effective when dealing with mature products. We propose a contracting scheme that can improve the decentralized chain profit in reliable delivery time settings. The salient modelling insight of this paper is that ignoring the randomness of delivery time trivializes the interaction between pricing and stocking decisions. On the other hand, from a managerial viewpoint, we establish that optimal pricing policies provide the means to increase revenue and also act as strategic tools for tackling uncertainty.