Showing papers by "Fuqiang Zhang published in 2015"

Delegation versus Control in Supply Chain Procurement Under Competition

Abstract: This paper studies the optimal component procurement strategies of two competing OEMs selling substitutable products. The OEMs outsource their production to a common contract manufacturer, who in turn needs an input from a component supplier. Each OEM may either directly procure the input from the component supplier, or delegate the procurement task to the contract manufacturer. We first analyze the OEMs' procurement game under a non-strategic supplier whose component price is exogenously given. It is found that symmetric equilibria arise for most situations, i.e., both OEMs either control or delegate their component procurement in equilibrium. Interestingly, despite the commonly-held belief that the contract manufacturer would be worse off as OEMs gain component procurement control, we show that the contract manufacturer may enjoy a higher profit. Then we study the OEMs' procurement game under a strategic supplier who can set its component price. We find that the supplier's strategic pricing behavior plays a critical role in the equilibrium procurement structure. In particular, in the equilibrium under strategic supplier, the larger OEM always uses delegation while the smaller OEM may use either delegation or control. By identifying the driving forces behind the OEMs' procurement choices, this research helps explain observed industry practices and offer useful guidelines for firms' component sourcing decisions.

Dynamic Capacity Management with General Upgrading.

Abstract: This paper studies a capacity management problem with upgrading. A firm needs to procure multiple classes of capacities and then allocate the capacities to satisfy multiple classes of customers tha...

Contracting for On-Time Delivery in the U.S. Influenza Vaccine Supply Chain

Abstract: Although influenza vaccine shortage is often attributed to low supply, it has been observed that even with abundant supply, a major shortage can still occur due to late delivery. In this paper, motivated by the influenza vaccine industry, we study a supply chain contracting problem in the presence of uncertainties surrounding design, delivery, and demand of influenza vaccine. In this supply chain, a manufacturer has insufficient incentive to initiate at-risk early production prior to the design freeze because it is a retailer who reaps the most benefits from selling more vaccines delivered on time. Anticipating that late delivery will lead to potential loss in demand, the retailer tends to reduce the order size, which further discourages the manufacturer from making an effort to improve its delivery performance. To break this negative feedback loop, a supply contract needs to achieve two objectives: incentivize at-risk early production and eliminate double marginalization. We find that two commonly observed supply contracts in practice, the Delivery-time-dependent Quantity Flexibility (D-QF) contract and the Late-Rebate (LR) contract, may fail to coordinate the supply chain because of the tension between these two objectives. To resolve such a tension, we construct a Buyback-and-Late-Rebate (BLR) contract and show that a properly designed BLR contract can not only coordinate the supply chain but also can provide full flexibility of profit division between members of the supply chain. Numerical experiments further demonstrate that the BLR contract significantly improves supply chain efficiency compared to the contracts used in the industry.

A Method for Analyzing Pollution Control Policies: Application To SO 2 Emissions in China

Abstract: Market-based pollution control mechanisms such as pollution levy and cap and trade have received increasing attention from both academics and practitioners. A good understanding of the optimal pollution price under these mechanisms is a premise for regulators to make sound pollution control policies. In this paper, we propose a method for deriving the optimal pollution price for a given pollution target. This method consists of two steps that integrate cost function estimation and market equilibrium analysis: First, historical data is used to estimate the pollution abatement cost functions of the polluters; second, market models are used to solve the equilibrium pollution price under each control mechanism. For illustration, we apply the method to investigate SO2 emission control policies in China, using a dataset of SO2 emissions and abatement costs from three major industry sectors (Electricity, Gas, and Water Supply; Manufacturing; and Mining). Our analysis shows that the optimal levy rate is significantly higher than the actual rate adopted by the Chinese government. For example, the optimal levy rate should be 4.92 RMB/kg, while the actual rate is 1.26 RMB/kg in 2010. As a result, the actual emission structure is much less efficient: The overall cost savings would be 49.7% for all three sectors during 2006-2010 if the optimal emission structure is achieved. These findings have useful policy implications for the Chinese government. In addition, the method may be applied to analyze control policies at different aggregate levels (for example, provincial economies) or for other pollutants (for example, CO2 and chemical oxygen demand).

Trade-In Remanufacturing, Customer Purchasing Behavior, and Government Policy

Abstract: Remanufacturing has been increasingly used in industry. To facilitate the collection of cores for remanufacturing, many firms offer rebates that allow repeat customers to trade in used products for upgraded ones at a discounted price. This paper studies the impact of strategic customer behavior on the economic and environmental values of such trade-in remanufacturing practice. There are several major findings. First, under trade-in remanufacturing, a firm may earn a higher profit with strategic customers than with myopic customers, which differs from the common belief that firms dislike forward-looking customer behavior due to its detrimental effect on profit. This is because strategic customers can anticipate the future price discount brought by the trade-in option, so when the revenue-generating effect of remanufacturing is strong enough, they might be willing to pay a higher first-period price than the myopic customers. Second, we show that strategic customer behavior may create a tension between profitability and sustainability: On one hand, by exploiting the forward-looking customer behavior, trade-in remanufacturing is more valuable to the firm with strategic customers than with myopic customers; on the other hand, with strategic customers, trade-in remanufacturing may have a negative impact on the environment and also on social welfare, since it may give rise to a significantly higher production quantity without improving customer surplus. Therefore, our research demonstrates that it is important to understand the interaction between trade-in remanufacturing and strategic customer behavior. Finally, to resolve the above tension, we study how a social planner (e.g., the government) should design a public policy to maximize social welfare. It has been shown that subsidizing remanufactured products alone may lead to undesired outcomes; however, the social optimum can be achieved by using a simple linear subsidy and tax scheme for all product versions.

An Empirical Investigation of Dynamic Ordering Policies

Abstract: Adaptive base stock policy is a well-known tool for managing inventories in nonstationary demand environments. This paper presents empirical tests of this policy using aggregate, firm-level data. First, we extend a single-item adaptive base stock policy in previous literature to a multi-item case. Second, we transform the policy derived for the multi-item case to a regression model that relates firm-level inventory purchases to firm-level sales and changes in sales forecasts. We focus on two research questions: Can the adaptive base stock policy explain cross-sectional ordering behaviors under sales growth? To the extent that the adaptive base stock policy fails to explain ordering behaviors under sales growth, are there frictions that explain such a finding? Our empirical results demonstrate disparities in ordering behaviors between firms experiencing high and moderate sales growth. Contrary to theoretical prediction, this implies that inventory purchases are a function of not only current sales and changes in sales forecast but also past sales growth. As potential explanations for this departure from theoretical prediction, we show that both future demand dynamics and inventory holding risks depend on past sales growth. In addition, we find that firms' inventory holding risks may also be affected by purchasing constraints imposed by supply chain contracts. Our results provide managerial implications for practitioners and inform future theoretical research. This paper was accepted by Martin Lariviere, operations management.

Asymmetric Cost Information and Enforcement in Supply Contract Design

Abstract: This paper studies a supply contracting problem where a buyer sources a product from a supplier to satisfy uncertain market demand. With the increasing length and complexity of today's global supply chains, the buyer may face two issues when designing the supply contract: adverse selection (i.e., the supplier's cost structure is private information) and lack of enforcement (i.e., the supplier's capacity investment is not enforceable). We derive the buyer's optimal contracting strategies and analyze their properties. We find that although the buyer's optimal mechanism is generally complex, it may reduce to a two-part tariff under certain conditions (i.e., a single, linear contract could be optimal for the buyer). Even when the two-part tariff is suboptimal, it performs nearly as well as the optimal mechanism for a wide range of situations. These findings indicate that the value of achieving enforceability and the value of using complex menu are negligible in such a supply chain setting. Therefore, our research demonstrates that the two-part tariff is an attractive option for buyers whose goal is to ensure supply while facing both cost uncertainty and enforcement issues. It also provides a new explanation for the prevalence of such simple contracts in practice.

To Share or Not to Share: Demand Forecast Sharing in a Distribution Channel

Abstract: This paper studies information sharing in a distribution channel where the manufacturer possesses better demand-forecast information than the downstream retailer. We examine three information-sharing formats: no information sharing (i.e., the manufacturer ex ante commits to not sharing its forecast), voluntary information sharing (i.e., the manufacturer makes the sharing decision ex post after receiving the forecast), and mandatory information sharing (i.e., the manufacturer is mandated to share its forecast). We characterize the equilibrium outcomes under the three sharing formats and investigate the firms’ preferences regarding these formats. It is shown that when the retailer is risk-neutral, both firms are indifferent between voluntary and mandatory sharing. Among the three formats, ex ante, the retailer prefers the no-sharing format whereas the manufacturer prefers the mandatory-sharing format. In addition, we find that a more accurate forecast benefits both firms under voluntary- and mandatory-sharing formats, but may hurt both firms under the no-sharing format. Finally, we show that risk aversion plays a critical role in the firms’ sharing decisions and the impact of forecast accuracy. Specifically, when the retailer is risk-averse, the manufacturer may prefer the no-sharing format over the voluntary-sharing format, and improving forecast accuracy may hurt both firms even under voluntary sharing.

Dynamic Capacity Management with General Upgrading

Abstract: This paper studies a capacity management problem with upgrading. A firm needs to procure multiple classes of capacities and then allocate the capacities to satisfy multiple classes of customers that arrive over time. A general upgrading rule is considered, i.e., unmet demand can be satisfied using multi-step upgrade. No replenishment is allowed and the firm has to make the allocation decisions without observing future demand. We first characterize the structure of the optimal allocation policy, which consists of parallel allocation and then sequential rationing. Specifically, the firm first uses capacity to satisfy the same-class demand as much as possible, then considers possible upgrading decisions in a sequential manner. We also propose a heuristic based on certainty equivalence control to solve the problem. Numerical analysis shows that the heuristic is fast and delivers close-to-optimal profit for the firm. Finally, we conduct extensive numerical studies to derive insights into the problem. It is found that under the proposed heuristic, the value of using sophisticated multi-step upgrading can be quite significant; however, using simple approximations for the initial capacity leads to negligible profit loss, which suggests that the firm's profit is not sensitive to the initial capacity decision if the optimal upgrading policy is used.