Knowledge that Transforms

We investigate the implications of collective and individual producer responsibility ( CPR and IPR , respectively) models of product take‐back laws for e‐waste on manufacturers’ design for product recovery (DfR) choices and profits, and on consumer surplus in the presence of product competition. We show that IPR offers superior DfR incentives as compared to CPR , and provides a level competitive ground. CPR may distort competition and allow free‐riding on DfR efforts to reduce product recovery costs. Thus, manufacturer preferences for IPR or CPR may differ because of the free‐riding implications under CPR , with even high‐end manufacturers having incentives to free‐ride under certain competitive conditions. The policy choice between IPR and CPR is not clear cut from an economic welfare perspective. This choice involves a comparison between the effects of superior recovery cost reduction through improved DfR under IPR and the operational cost‐efficiency under CPR .

Some retailers of seasonal products adopt weather‐conditional rebate programs to induce early sales and increase profits. In such promotions, customers who buy the product in an advance preselling period are offered rebates if a pre‐specified weather condition is realized during the later normal selling season. We investigate the potential benefits of these programs for retailers. We show that the weather‐conditional rebate program can increase sales by price discriminating among a customer's post‐purchase states. Taking advantage of the early sales, it can also reduce the inventory holding cost and ordering cost, and hence can increase the retailer's expected profits. In addition, we numerically investigate the sensitivity of the rebate program's effectiveness to the model parameters and illustrate its advantages over an advance‐discount policy.

We study the design of extended warranties in a supply chain consisting of a manufacturer and an independent retailer. The manufacturer produces a single product and sells it exclusively through the retailer. The extended warranty can be offered either by the manufacturer or by the retailer. The party offering the extended warranty decides on the terms of the policy in its best interest and incurs the repair costs of product failures. We use game theoretic models to answer the following questions. Which scenario leads to a higher supply‐chain profit, the retailer offering the extended warranty or the manufacturer? How do the optimum price and extended warranty length vary under different scenarios? We find that, depending on the parameters, either party may provide better extended warranty policies and generate more system profit. We also compare these two decentralized models with a centralized system where a single party manufactures the product, sells it to the consumer, and offers the extended warranty. We also consider an extension of our basic model where either the manufacturer or the retailer resells the extended warranty policies of a third party (e.g., an independent insurance company), instead of offering its own policy.

Whether to invest in process development that can reduce the unit cost and thereby raise future profits or to conserve cash and reduce the likelihood of bankruptcy is a key trade‐off faced by many startup firms that have taken on debt. We explore this trade‐off by examining the production quantity and cost reducing R&D investment decisions in a two period model wherein a startup firm must make a minimum level of profit at the end of the first period to survive and operate in the second period. We specify a probabilistic survival measure as a function of production and investment decisions to track and manage the risk exposure of the startup depending on three key market factors: technology, demand, and competitor's cost. We develop managerial insights by characterizing how to create operational hedges against the bankruptcy risk: if a startup makes a “conservative” investment decision, then it also selects an optimal quantity that is less than the monopoly level and hence sacrifices some of first period expected profits to increase its survival chances. If it decides to invest “aggressively,” then it produces more than the monopoly level to cover the higher bankruptcy risk. We also illustrate that debt constraint shrinks the decision space, wherein such process investments are viable.

Online marketplaces, such as those operated by Amazon, have seen rapid growth in recent years. These marketplaces serve as an intermediary, matching buyers with sellers, whereas control of the good is left to the seller. In some cases, e.g., the Amazon marketplace system, the firm that owns and manages the marketplace system will also sell competing products through the marketplace system. This creates a new form of channel conflict, which is a focus of this article. We consider a setting in which a marketplace firm operates an online marketplace through which retailers can sell their products directly to consumers. We consider a single retailer, who currently sells its product only through its own website, but who may choose to contract with Amazon to sell its product through the marketplace system. Selling the product through the marketplace expands the available market for the retailer, but comes at some expense, e.g., a fixed participation fee or a revenue sharing requirement. Thus, a key question for the retailer is whether she should choose to sell through the marketplace system, and if so, at what price. We analyze the optimal decisions for both the retailer and the marketplace firm and characterize the system equilibrium.

Drawing on behavioral research, we construct a multi‐period model with which to examine the role of trust and other social characteristics in a supply chain. Specifically, we focus on trust building in the context of a salesperson who acts as a representative of a manufacturer and shares demand forecast information with a retailer. The actions of the salesperson affect both her immediate economic gain and her future credibility as determined by retailer's trust. Our analysis reveals that, in such environments, although salespersons of widely varying types (e.g., honest, self‐serving, benevolent, loyal) lie some extent about their forecast information, they tend to be trusted in long relationships, provided their forecasting accuracy is higher than that of the retailer. Furthermore, while the presence of a salesperson can improve the profits of both the retailer and manufacturer, there are cost structures under which the manufacturer is better off without a salesperson. Finally, we make the general observation that the appropriate salesperson compensation scheme depends on her social characteristics, and the specific observation that when the salesperson cares for the retailer, the linear compensation scheme commonly suggested in the literature as the optimal compensation scheme for the salesperson is no longer optimal.