Do Unlisted Targets Sell at Discounts?

Academic literature, practitioners, courts, and regulators routinely assert that both private and subsidiary targets sell at discounts relative to public targets. However, the empirical evidence to support this conclusion is thin. Our work alters the methodology from prior research to avoid biases due to both one-sided sample truncation and Jensen’s inequality. Following these changes, we find no evidence that unlisted targets sell at discounts. Our results hold under a number of different approaches and after controlling for known determinants of acquisition pricing.

Acquisition Pricing and Inventory Decisions on Dual-Source Spare-Part System with Final Production and Remanufacturing

The life spans of durable goods are longer than their warranty periods. To satisfy the service demand of spare parts and keep the market competition advantage, enterprises have to maintain the longer inventory planning of spare parts. However, how to obtain a valid number of spare parts is difficult for those enterprises. In this paper, we consider a spare-part inventory problem, where the inventory can be replenished by two ways including the final production order and the remanufacturing way. Especially for the remanufacturing way, we consider the acquisition management problem of used products concerning an acquisition pricing decision. In a multiperiod setting, we formulate the problem into a dynamic optimization problem, where the system decisions include the final production order and acquisition price of used products at each period. By stochastic dynamic programming, we obtain the optimal policy of the acquisition pricing at each period and give the optimal policy structure of the optimization problem at the first period. Then, a recursion algorithm is designed to calculate the optimal decisions and the critical points in the policy. Finally, the numerical analyses show the effects of demand information and customer’s sensitive degree on the related decisions and the optimal cost.

Dynamic acquisition pricing policy under uncertain remanufactured-product demand

Purpose – The purpose of this paper is to investigate the dynamic acquisition pricing strategy for collecting used products (also known as cores or returns) in a finite planning horizon. In particular, this paper studies a cost-minimization model in which a firm offers acquisition price that impacts the quantity of the returns, and remanufactures the used product to satisfy the customer demand. Design/methodology/approach – This paper uses multi-period stochastic dynamic programming theory to model a remanufacturing system that faces the random demand for remanufactured products. The number of the returns at each period is uncertain and increases linearly with the acquisition price offered. Findings – The study shows that when the uncertainty of demand for remanufactured products increases, the remanufacturer should hold a higher core stock level to minimize the expected total cost and thus a higher acquisition price is needed to attract returns. However, given demand uncertainty, the optimal price decreases in the initial core stock level in each period. It also indicates that the optimal acquisition price increases in the variance of the returns, but decreases in the mean of the returns. Practical implications – The findings suggest that a remanufacturer could reduce the expected total cost by adjusting the acquisition price according to the number of returns periodically. Originality/value – Introducing the impact of supply uncertainty on the acquisition price of used products, this paper uses a multi-period dynamic model, instead of single period model in previous studies, to examine the remanufacturer’s dynamic acquisition pricing policy.