Knowledge that Transforms

To avoid inventory risks, manufacturers often place rush orders with suppliers only after they receive firm orders from their customers (retailers). Rush orders are costly to both parties because the supplier incurs higher production costs. We consider a situation where the supplier's production cost is reduced if the manufacturer can place some of its order in advance. In addition to the rush order contract with a pre‐established price, we examine whether the supplier should offer advance‐order discounts to encourage the manufacturer to place a portion of its order in advance, even though the manufacturer incurs some inventory risk. While the advance‐order discount contract is Pareto‐improving, our analysis shows that the discount contract cannot coordinate the supply chain. However, if the supplier imposes a pre‐specified minimum order quantity requirement as a qualifier for the manufacturer to receive the advance‐order discount, then such a combined contract can coordinate the supply chain. Furthermore, the combined contract enables the supplier to attain the first‐best solution. We also explore a delegation contract that either party could propose. Under this contract, the manufacturer delegates the ordering and salvaging activities to the supplier in return for a discounted price on all units procured. We find the delegation contract coordinates the supply chain and is Pareto‐improving. We extend our analysis to a setting where the suppliers capacity is limited for advance production but unlimited for rush orders. Our structural results obtained for the one‐supplier‐one‐manufacturer case continue to hold when we have two manufacturers.

As waste from used electronic products grows steadily, manufacturers face take‐back regulations mandating its collection and proper treatment through recycling, or remanufacturing. Environmentalists greet such regulation with enthusiasm, but its effect on remanufacturing activity and industry competition remains unclear. We research these questions, using a stylized model with an original equipment manufacturer (OEM) facing competition from an independent remanufacturer (IR). We examine the effects of regulation on three key factors: remanufacturing levels, consumer surplus, and the OEM profit. First, we find that total OEM remanufacturing actually may decrease under high collection and/or reuse targets, meaning more stringent targets do not imply more remanufacturing. Consumer surplus and the OEM profit, meanwhile, may increase when OEM‐IR competition exists in a regulated market. Finally, through a numerical study, we investigate how total welfare changes in the collection target, what happens when the cost of collection is not linear, and what happens when IR products are valued differently by consumers.

A growing number of companies install wind and solar generators in their energy‐intensive facilities to attain low‐carbon manufacturing operations. However, there is a lack of methodological studies on operating large manufacturing facilities with intermittent power. This study presents a multi‐period, production‐inventory planning model in a multi‐plant manufacturing system powered with onsite and grid renewable energy. Our goal is to determine the production quantity, the stock level, and the renewable energy supply in each period such that the aggregate production cost (including energy) is minimized. We tackle this complex decision problem in three steps. First, we present a deterministic planning model to attain the desired green energy penetration level. Next, the deterministic model is extended to a multistage stochastic optimization model taking into account the uncertainties of renewables. Finally, we develop an efficient modified Benders decomposition algorithm to search for the optimal production schedule using a scenario tree. Numerical experiments are carried out to verify and validate the model integrity, and the potential of realizing high‐level renewables penetration in large manufacturing system is discussed and justified.

Recent research indicates that consumers hold significant concerns about the quality of remanufactured products. To better understand this phenomenon, this manuscript combines surveys and experimental studies to identify the antecedents of perceived quality—in the form of perceived risk of functionality and cosmetic defects—and their significant impact on consumers' willingness to pay (wtp) for remanufactured electronics products. The study also controls for alternative explanations for wtp suggested in the literature, such as consumers' wtp for new products, environmental beliefs, disgust aversion toward used products, brand perceptions, risk aversion, and various demographic traits. Importantly, the study empirically estimates the magnitude and distribution of discount factors for remanufactured electronics products—the ratio between wtp for a remanufactured product and wtp for a corresponding new product—among consumers. Finally, the manuscript analytically compares a monopolist's decision to include remanufactured products in its portfolio under both the empirically derived discount factor distributions and the classical linear demand model, which assumes constant discount factors. Interestingly, the classical linear demand model remains reasonably robust for high‐level insights, such as the presence of cannibalization and market expansion effects. However, the analytical model that uses the empirically‐derived distributions of discount factors demonstrates significantly higher profitability than predicted by the classical linear model. This fundamental link between risk perceptions, wtp for remanufactured products, and profitability provides new insights on how to manage demand and product pricing in closed‐loop supply chains.

We consider manufacturer rebate competition in a supply chain with two competing manufacturers selling to a common retailer. We fully characterize the manufacturers’ equilibrium rebate decisions and show how they depend on parameters such as the fixed cost of a rebate program, market size, the redemption rate of rebate, the proportion of rebate‐sensitive consumers in the market and competition intensity. Interestingly, more intense competition induces a manufacturer to lower rebate value or stop offering rebate entirely. Without rebate, it is known that more intense competition hurts the manufacturers and benefits the retailer. With rebate, however, more intense competition could benefit the manufacturers and hurt the retailer. We find similar counterintuitive results when there is a change in some other parameters. We also consider the case when the retailer subsidizes the manufacturers sequentially to offer rebate programs. We fully characterize the retailer's optimal subsidy strategy, and show that subsidy always benefits the retailer but may benefit or hurt the manufacturers. When the retailer wants to induce both manufacturers to offer rebate, he always prefers to subsidize the manufacturer with a higher fixed cost first. Sometimes the other manufacturer will then voluntarily offer rebate even without subsidy.

Research on buyer–supplier relationships (BSRs) has often focused on only one side of the relationship and, thus, has tended to overlook asymmetries. Yet, a buyer (supplier) may often deal with a bigger supplier (buyer) or one that has higher levels of trust, respect, and reciprocity. Therefore, we examined how two types of asymmetries—size and relational capital—affect perceived opportunism and performance. We used dyadic data from 106 buyers and their matched suppliers gathered from a survey and an archival database. The results demonstrate that the degree and direction of both asymmetries affect the BSR. Our results also reveal that an imbalance of relational capital in a firm's favor may have the opposite effect from that intended. In other words, the firm's counterpart perceives more, rather than less, firm opportunism. The results also suggest that a buyer observes lower benefits in the presence of size asymmetry, whereas the supplier's perception of benefits is unaffected. Thus, our research represents a significant step forward in understanding BSRs and asymmetries by (i) bringing attention to two key asymmetries inherent in BSRs and (ii) showing that these asymmetries are not unidirectional in their influence on perceived opportunism and performance.

Discrete‐choice models are widely used to model consumer purchase behavior in assortment optimization and revenue management. In many applications, each customer segment is associated with a consideration set that represents the set of products that customers in this segment consider for purchase. The firm has to make a decision on what assortment to offer at each point in time without the ability to identify the customer's segment. A linear program called the Choice‐based Deterministic Linear Program ( CDLP) has been proposed to determine these offer sets. Unfortunately, its size grows exponentially in the number of products and it is NP‐hard to solve when the consideration sets of the segments overlap. The Segment‐based Deterministic Concave Program with some additional consistency equalities ( SDCP+) is an approximation of CDLP that provides an upper bound on CDLP's optimal objective value. SDCP+ can be solved in a fraction of the time required to solve CDLP and often achieves the same optimal objective value. This raises the question under what conditions can one guarantee equivalence of CDLP and SDCP+. In this study, we obtain a structural result to this end, namely that if the segment consideration sets overlap with a certain tree structure or if they are fully nested, CDLP can be equivalently replaced with SDCP+. We give a number of examples from the literature where this tree structure arises naturally in modeling customer behavior.

In the automotive industry, many firms source key components from different suppliers, even though the components may function interdependently. In this study, we investigate how component level interdependence impacts quality performance and analyze how various operational factors moderate this relation. We synthesize information from several case studies to model the quality challenges faced by an automotive firm. For several sub‐assemblies that go into its products, the firm sourced key components from two different suppliers. The sub‐assemblies would fail whenever a component fails, but due to interdependent operations, failure of one component could cause the failure of the other. The firm found it challenging to improve the suppliers' quality performance as it was difficult to trace the failures to specific components. Our analysis reveals that – (i) the impact of interdependence is governed by the supply chain structure: reducing the interdependence between components improves quality when suppliers provide the components, but reducing interdependence worsens quality when the firm manufactures the entire sub‐assembly; and (ii) the relation between interdependence and quality performance is moderated by factors such as penalties, production costs, and interdependence costs. Additionally, we find that quality performance is lower when the firm outsources the components than when the firm manufactures the entire sub‐assembly. We identify coordinating mechanisms that leverage incentives and penalties to bridge the quality performance gap.

The increasing pervasiveness of social networks allows users to share purchase behaviors with their online friends. In this study, we examine optimal pricing strategies of a monopolistic firm using an analytical model that accounts for behavioral observational learning in social networks. We show that a seller could potentially control the information available to future customers and induce behavioral observational learning, using an information‐revealing pricing strategy. This result suggests that offering introductory discounts is not always an effective method to boost purchases in social networks. It could prevent the behavioral observational learning that would increase future customers' willingness to pay.