本文精选了生产和运营管理领域国际顶刊《Production and Operations Management》近期发表的论文，提供生产和运营管理研究领域最新的学术动态。

3D Printing-as-a-Service: An Economic Analysis of Pricing and Cocreation

原刊和作者：

Production and Operations Management Volume 33, Issue 7

Tarun Jain （Indian Institute of Management Bangalore）

Jishnu Hazra （Indian Institute of Management Bangalore）

Ram Gopal （Warwick Business School）

Abstract

Three-dimensional (3D) printing technology has opened up possibilities for product design collaborations between device providers and customers. To enable an environment of cocreation, device providers are now renting 3D printers via the 3D-as-a-Service (3DaaS) model. Although prior research has examined pricing and quality issues in the traditional manufacturing setup, these studies have not analyzed such decisions in the 3D printing supply chain setting, where end users possess the ability to customize product designs. Therefore, several important questions remain unanswered from the perspective of the 3D printing device provider. For example, what is the appropriate pricing model for providing 3DaaS? How do factors such as the extent of design customization and the complexity influence the pricing strategy of the 3DaaS firm? Our analysis shows that if the customers’ impact on the product quality is relatively high or low, the pay-per-build pricing model generates a higher profit than the fixed-fee pricing model. Interestingly, we also find that if customers frequently print highly intricate product designs, the firm might choose the pay-per-build pricing model, only if the likelihood of design failure for these complex structures is low. Otherwise, the firm might opt for the fixed-fee pricing model.

Link: https://doi.org/10.1177/10591478241257660

Admission Control in Multi-server Systems Under Binary Reward Structure

原刊和作者：

Production and Operations Management Volume 33, Issue 7

Wei Liu （University of Science and Technology of China）

Vidyadhar G Kulkarni （The University of North Carolina at Chapel Hill）

Abstract

We study a multi-server queueing system where a customer is satisfied (and generates a unit revenue) if their queueing time is at most a given constant. If the queueing time of the admitted customer exceeds this constant, the customer gets served, but is unsatisfied and generates no revenue. Such queueing systems arise in the context of modeling service systems where excessive delays are of concern. A key challenge is how to design an admission control policy to maximize the number of satisfied customers per unit time in the long run, assuming that we can observe the number of customers in the system at any time. We call this the binary reward structure system and show that a threshold-type admission policy is optimal. The optimal threshold policy has to be computed numerically. Hence we propose a square-root admission policy to approximate the optimal admission control policy, and compare the performance of these two policies. We derive an analytical upper bound on the performance of optimal admission control policy by deriving an optimal admission policy assuming we have full information over the queueing time of the admitted customers. This is equivalent to a queueing system where customers abandon the queue (i.e., leave without service) if their queueing time exceeds the given constant. We demonstrate that the optimal policy that includes customer abandonment, or alternatively, the optimal policy under full information, the optimal threshold policy, and the square-root admission policy, all exhibit identical performance in the asymptotic regions of the parameter space. Our numerical results indicate that the worst optimality gap of the square-root admission policy is within 3.9% of the optimal revenue, and implementing the square-root admission policy in the observable queueing system leads to a revenue loss that is at most 5.6% of the maximum possible revenue rate in the full information system. We also compare the binary reward structure with the more common linear reward structure where the system incurs holding cost per unit queueing time per customer. In addition, we also show that the analysis based on queueing time is applicable to the system time as well.

Link: https://doi.org/10.1177/10591478241254855

Competitive Dynamic Pricing Under Capacity Constraints: An Experimental Study

原刊和作者：

Production and Operations Management Volume 33, Issue 7

Bahriye Cesaret （Ozyegin University）

Armagan Bayram （University of Michigan at Dearborn）

Abstract

Keeping up with competitors’ prices is one of the top operational challenges in pricing. However, competitive interactions in revenue management have not received much research attention in the past due to their complexity. We conduct a series of laboratory experiments to investigate the dynamic pricing behavior of two capacity-constrained firms under competition. Our experiments initially control for strategic interactions between the sellers and then allow for them. To gain a broader understanding, we also manipulate demand uncertainty and the expected market size. Our results confirm the dependency of dynamic pricing decisions on the competitor's behavior. We find that the theory is much more forgiving—in the sense that it predicts a lower level of competition among the sellers—than what we actually observe in the laboratory. The modeling literature indicates that the seller with the lower capacity has a competitive advantage, but our results reveal the opposite. Further, there is potential for high-capacity sellers to benefit from competition. Sellers tend to underprice (resp., overprice) their units at the beginning (resp., end) of a selling season. Also, competition lasts longer than the theory predicts, and customers benefit from the biases of the competing sellers. The higher-capacity seller following the best-response policy is not harmed due to the biases of the competitor. However, the lower-capacity seller's performance is greatly influenced by the competitor's degree of rationality.

Link: https://doi.org/10.1177/10591478241255667

Counterfeit Competition With Strategic Consumers

原刊和作者：

Production and Operations Management Volume 33, Issue 7

Yucheng Ding （Wuhan University）

Xu Guan （Huazhong University of Science and Technology）

Jiannan Ke （Wuhan University）

Abstract

This article investigates competition between a branded firm selling a durable good over two periods and a deceptive counterfeiter entering the market in the second period. The two firms engage in a price signaling game in which the branded firm designs its price strategy over two periods, and strategic consumers decide whether to buy the authentic product upfront or wait until the second period. We find that the branded firm may benefit from the counterfeit competition if the quality gap between the two products is sufficiently large. The intuition is that the branded firm would charge a high second-period price to signal its authenticity, inducing more consumers to buy the genuine product upfront. This strategy allows the branded firm to increase its first-period price and demand simultaneously, thus effectively mitigating the time-inconsistency problem. Otherwise, when the quality gap is small, counterfeit competition leads to reduced profits for the authentic product. These results remain robust throughout several extensions of the base model, including partially informed or naive consumers, asymmetric retail channels, post-purchase regret, and endogenized counterfeit.

Link: https://doi.org/10.1177/10591478241252149

Managing Hybrid Manufacturing/Remanufacturing Inventory Systems With Random Production Capacities

Production and Operations Management Volume 33, Issue 7

Xiting Gong （CUHK Business School）

Suting Liu （University of Science and Technology of China）

Abstract

In this article, we consider hybrid manufacturing/remanufacturing inventory systems that produce a single product to satisfy demands over a finite planning horizon. In each period, the firm receives random demand and returns of end-of-life products. A serviceable product can be manufactured from ample raw materials or remanufactured from a returned product. The two operations possess random dedicated capacities. The firm’s objective is to minimize the expected total discounted cost over the planning horizon. We partially characterize the firm’s optimal inventory policy when the two capacities are positively dependent and completely characterize it when only one capacity is random. When there is ample manufacturing capacity, we connect the model with an auxiliary dual-sourcing inventory model and derive a more detailed structure of the optimal policy. Finally, our numerical study provides actionable insights into the effects of random capacities. Among others, we find that approximating a slightly/moderately variable remanufacturing capacity as its deterministic mean capacity or ignoring the correlation between two random capacities under a multi-period setting incurs a limited cost to the firm.

Link: https://doi.org/10.1177/10591478241252357