Jianbin Li

Optimal dynamic pricing of inventories with stochastic demand and discounted criterion

We consider a continuous time dynamic pricing problem for selling a given number of items over a finite or infinite time horizon. The demand is price sensitive and follows a non-homogeneous Poisson process. We formulate this problem as to maximize the expected discounted revenue and obtain the structural properties of the optimal revenue function and optimal price policy by the Hamilton–Jacobi–Bellman (HJB) equation. Moreover, we study the impact of the discount rate on the optimal revenue function and the optimal price. Further, we extend the problem to the case with discounting and time-varying demand, the infinite time horizon problem. Numerical examples are used to illustrate our analytical results.

Joint optimisation of order batching and picker routing in the online retailer’s warehouse in China

Order picking is the core of warehouse operations and considerable researches have been conducted on improving its efficiency. In this paper, we aim at the joint optimisation of order batching and picker routing based on a famous and typical online retailer of China, which mainly focuses on fast-moving consumer goods. An integer programming is formulated to minimise the total travelling distance involving with order batching and picker routing. In the stage of order batching, an effective batching procedure based on similarity coefficient which is measured by overlapping channels between orders is proposed. In the stage of picker routing, an improved ant colony optimisation algorithm with local search is proposed. Based on those simulated orders generated by actual transaction data, numerical experiments are conducted to verify the performance of the algorithm we proposed. Results show that the proposed joint optimisation algorithm has potential advantages under various order sizes and order structures, which implies that it is effective and efficient particularly in the online retailing of fast-moving consumer goods.

Bullwhip effect and supply chain costs with low- and high-quality information on inventory shrinkage

Inventory inaccuracy is the mismatch between the recorded inventory and the physical inventory, which is severe and widespread in industry. A few studies have investigated the bullwhip effect with the existence of inventory inaccuracy. The development of information technologies has provided companies with access to accurate inventory information in real time. This will surely affect the bullwhip effect and supply chain costs. The aim of this paper is to build an analytical model to systematically investigate these effects. We consider a retailer–manufacturer supply chain in which the retailer faces inventory shrinkage, which is the main cause of inventory inaccuracy. Both the situations with accurate real-time inventory information, i.e., high-quality information, and the situation with statistical inventory information, i.e., low-quality information are studied. We examine the relationships between the bullwhip effect, information distortion and supply chain costs with different levels of information quality. The results of our analysis enrich the existing literature on the bullwhip effect. First, we show that the bullwhip effect is magnified along the chain when higher-quality information on inventory shrinkage – specifically real-time rather than statistical data – is obtained. Second, we show that the magnification of the bullwhip effect does not necessarily result in higher costs. Third, we demonstrate that higher-quality information increases the benefits of information sharing. Our paper provides new insights into the causes, extent and economic dynamics of order variability in the presence of inventory inaccuracy, and may thus suggest ways of more effectively managing the bullwhip effect and inventory.

Analysis of gray markets in differentiated duopoly

In recent years, gray markets have become a significant phenomenon in the business practice. This paper investigates the gray markets issues in differentiated duopoly case by considering quantity competition among firms. We develop a game-theoretic model and provide equilibrium results for three scenarios, i.e. the benchmark scenario ‘no gray market’, the scenario ‘parallel imports act as a buffer against a follower’s product’ and the scenario ‘gray markets stimulate the competition’. By the analysis of the equilibrium results, some important managerial insights are obtained. Finally, by comparison of the equilibrium results among different scenarios, we study the impact of gray markets on manufacturers’ optimal strategies and profits in differentiated duopoly.

Optimal Remanufacturing and Pricing Strategies Under Name-Your-Own-Price Auctions and Stochastic Demand

In this paper, we study recycling, remanufacturing, and pricing strategies of a manufacturer in a closed-loop supply chain. Different from traditional list-price transaction, a name-your-own-price auction is introduced into the recycling process where consumers offer a bid for their own used items and the manufacturer decides whether to accept the bid. We first analyze the consumers’ behavior and find that their bids increase with the dealing cost. Next, we build a newsvendor framework to investigate the manufacturer’s optimal manufacturing with pricing strategies and find that the stocking factor influences the recycling quantity and manufacturing policy. Moreover, we find that a larger salvage value motivates the manufacturer to set a higher stocking factor and thus recycle more as well as manufacture new products. We further investigate the effect of the demand uncertain level and the dealing cost on the system.

Joint optimisation of tracking capability and price in a supply chain with endogenous pricing

Abstract Tracking systems have been widely used to resolve the issues of product recall and food safety. Thus far, few researches have been done on designing the tracking capability from the perspective of supply chain. In this paper, using the traceable unit size at the manufacturer level to measure the tracking capability, we propose a non-convex non-linear programming to jointly optimise the tracking capability and price considering the tracking cost and recall cost in a supply chain with endogenous pricing. Results show that, in both centralised and decentralised supply chains, there is a unique tracking capability and retailing/wholesale price with closed-form solutions to optimise the supply chain profit. When the cost ratio (unit tracking cost/unit recall cost) is sufficiently large and small, the optimal tracking strategy is barcode tracking and unit tracking, respectively, and otherwise, the optimal tracking strategy is batch tracking with an economic traceable unit size which depends on the cost ratio, quality inspection threshold, supply defection rate and the supplier’s tracking capability. Furthermore, in the context of large and small cost ratio, we find that improving tracking capability will enlarge and mitigate the effect of double marginalisation, respectively. In particular, we find that the strict tracking regulation policy is more robust than the subsidy policy to improve the supply chain tracking capability.

Fairness of extra-gain guilty in performance of supply chain and contract design

Considering a one-supplier and two-retailer supply chain setting in which the supplier makes contacts with retailers in sequence based on FCFS (first–come–first-service) principle, the authors investigate the marginal effect of extra-gain guilty fairness concerns of supply chain members on the contract design, supply chain’s profit and profit distribution. When the supplier considers distributional fairness of loss aversion and extra-gain guilty, extra-gain guilty concern reduces the optimal wholesale and retail price, and improves supply chain performance. When the first or the second retailer considers distributional fairness and peer-induced fairness, extra-gain guilty concerns decrease the optimal wholesale and retail price but increase the profit of all supply chain members only when the level of loss aversion is large enough and the level of extra-gain guilty is less than 1/2. However, when the level of loss aversion is small and the level of extra-gain guilty is less than 1/2, extra-gain guilty has no influence on supply chain performance. The analysis reveals that the supply chain performance can be further improved by considering fairness of extra-gain guilty.

Direct subsidy incentive capacity restoration contract under supply disruption risk

Consider a supply chain consists of a supplier and a buyer. The supplier faces a risk of disruption and could rebuild the capacity if he has invested before the disruption. To motivate the supplier to invest and share the burden of capacity restoration, the buyer adopts a direct subsidy incentive contract. For this incentive contract, the buyer provides financial subsidy to share the capacity restoration cost of the supplier if there is a disruption. We also consider contract timing problem. We compare the Ex Post commitment strategy (the incentive contract is offered after disruption) and Ex Ante commitment strategy (the incentive contract is offered before disruption). We find that Ex Ante commitment strategy dominates Ex Post commitment strategy because it provides a wider parameter range for the investment decision of the supplier, and leads to profit improvement for both the supplier and the buyer.

The optimal strategies in a two-echelon supply chain with risk-aversion and customers rebates

Consider a supply chain consisting of one risk-averse retailer and one risk-neutral manufacturer with endogenous manufacturer rebates (rebate to consumers), and the demand faced by the retailer is stochastic, price-dependent. We adopt Conditional Value-at-Risk (CVaR) as the retailers decision criterion. The demand uncertainty is assumed to be multiplicative, and the expected demand depends on the effective price of the product. We characterize the manufacturer and retailers optimal strategies simultaneously. We show the existence of Nash equilibrium between the manufacturer and the risk-averse retailer.