Optimal Replenishment Strategy for Inventory Mechanism with a Known Price Increase and Backordering in Finite Horizon

For the finite horizon inventory mechanism with a known price increase and backordering, based on minimizing the inventory cost, we establish two mixed integer optimization models. By buyer’s cost analysis, we present the closed-form solutions to the models, and by comparing the minimum cost of the two strategies, we provide an optimal ordering policy to the buyer. Numerical examples are presented to illustrate the validity of the model, and sensitivity analysis on major parameters is also made to show some insights to the inventory model.

Optimal Ordering Policy for Retailers with Bayesian Information Updating in a Presale System

In this study, we investigate inventory allocation and pricing strategies for retailers by incorporating demand information into the issue of inventory allocation during the presale period. In a presale system, retailers offer presale goods at a price lower than the retail price. By offering products at a discount, retailers may attract additional demand. In addition, this system enables retailers to reduce the uncertainty of market demand and establish a strategy for inventory allocation based on the results of presales. A Bayesian approach was employed to analyze and update demand information, and inventory allocation was formulated as a newsvendor problem to determine the optimal policy that maximizes retailer profit . A numerical analysis was conducted to validate the effectiveness of the proposed strategy. Results suggest that the proposed strategies can support retailers by more accurately predicting demand and achieving higher profits with less inventory. Furthermore, retailers can experience greater benefits from risk-averse customers than from risk-neutral customers.

Optimizing voting order on sequential juries: a median voter theorem and beyond

We consider an odd-sized “jury”, which votes sequentially between two equiprobable states of Nature (say A and B, or Innocent and Guilty), with the majority opinion determining the verdict. Jurors have private information in the form of a signal in $$[-1,+1]$$ [ - 1 , + 1 ] , with higher signals indicating A more likely. Each juror has an ability in [0, 1], which is proportional to the probability of A given a positive signal, an analog of Condorcet’s p for binary signals. We assume that jurors vote honestly for the alternative they view more likely, given their signal and prior voting, because they are experts who want to enhance their reputation (after their vote and actual state of Nature is revealed). For a fixed set of jury abilities, the reliability of the verdict depends on the voting order. For a jury of size three, the optimal ordering is always as follows: middle ability first, then highest ability, then lowest. For sufficiently heterogeneous juries, sequential voting is more reliable than simultaneous voting and is in fact optimal (allowing for non-honest voting). When average ability is fixed, verdict reliability is increasing in heterogeneity. For medium-sized juries, we find through simulation that the median ability juror should still vote first and the remaining ones should have increasing and then decreasing abilities.

Behavioral operations effect of fairness and unfairness concern in the decision of the supply chain production-inventory system

Purpose The purpose of this paper is to investigate the behavioral operations effect in production inventory decision of supply chain consisting of one manufacturer and one buyer, and analyze how the unfairness concerns impact the decision of production inventory in a supply chain system. Design/methodology/approach First, a model without the buyer’s unfairness concern is established; then, advantage unfairness concern and disadvantage unfairness concern behavior of buyer are taken into account in the production inventory system. The authors analyze how advantage unfairness concern and disadvantage unfairness concern impact the optimal decisions and channel coordination. Findings The result shows several important conclusions. First, the buyer’s optimal ordering quantity and expected utility show opposing trend when the buyer has advantage unfairness concern. Second, the stronger bargaining power of the manufacturer results in an increasing buyer’s optimal ordering quantity under the advantage unfairness concern case, but decreasing under the disadvantage unfairness concern case. Third, the supply chain production-inventory can be coordinated under advantage unfairness concern case, but cannot be coordinated under disadvantage unfairness concern. Practical implications The study can provide to practitioners with important implications that when the vendor or the buyer in supply chain wants to make the decision of inventory replenishment, taking unfairness concerns into account will lead to different results. Therefore, to effectively improve the operations performance of supply chain, partners of the supply chain should not only care about their own interest, but also need to consider the fairness concern of the other partner, reflecting the cooperation consciousness of supply chain management. Originality/value This paper contributes to the new field of creative management–behavioral operations, offering managerial implications for the decision and optimization of supply chain production-inventory problem.