Dynamic Pricing and Lead‐Time Policies for Make‐to‐Order Systems*

Make‐to‐order firms use different approaches for managing their lead‐times and pricing in the face of changing market conditions. A particular firm's approach may be largely dictated by environmental constraints. For example, it makes little sense to carefully manage lead‐time if its effect on demand is muted, as it can be in situations where leadtime is difficult for the market to gauge or requires investment to estimate. Similarly, it can be impractical to change capacity and price. However, environmental constraints are likely to become less of an issue in the future with the expanding e‐business infrastructure, and this trend raises questions into how to manage effectively the marketing mix of price and lead‐time in a more “friction‐free” setting. We study a simple model of a make‐to‐order firm, and we examine policies for adjusting price and capacity in response to periodic and unpredictable shifts in how the market values price and lead‐time. Our analysis suggests that maintaining a fixed capacity while using lead‐time and/or price to absorb changes in the market will be most attractive when stability in throughput and profit are highly valued, but in volatile markets, this stability comes at a cost of low profits. From a pure profit maximization perspective, it is best to strive for a short and consistent lead‐times by adjusting both capacity and price in response to market changes.     

The Roles of Supply Chain Intelligence and Adaptability in New Product Launch Success

Many new product introductions continue to be unsuccessful, and while researchers have studied product development processes, relatively few studies directly address new product launch. We do so in the present research and posit that supply chain intelligence, defined as technological and competitive knowledge sourced and integrated from suppliers, customers, and competitors, plays an important role in explaining new product launch success. We further employ the knowledge‐based view to theorize that both supply chain adaptability and product innovation capability act as important mediators of the effects of supply chain intelligence on new product launch success and firm financial performance. While the former capability refers to a firm's ability to quickly adjust its supply chain to react to market and product design changes, the latter refers to the firm's proficiency in developing innovative new products. We test hypothesized relationships among these factors utilizing data collected in a survey of 229 U.S. manufacturing firms. Results point to the central role of supply chain adaptability in capturing the benefits of supplier technological intelligence for enhanced product innovation capability, new product launch success, and firm financial performance. In contrast, product innovation capability serves as the generative means by which customer and competitor intelligence is translated into more successful new product launches, which, in turn, produce superior firm financial performance. Overall, these findings contribute to a better understanding of factors that can explain why certain product launches are more successful than others, and offer practical insights for appropriate investments in the development of related knowledge resources.     

Push and Pull Contracts in a Local Supply Chain with an Outside Market*

Wholesale price contracts are widely studied in a single supplier‐single retailer supply chain, but without considering an outside market where the supplier may sell if he gets a high enough price and the retailer may buy if the price is low enough. We fill this gap in the literature by studying push and pull contracts in a local supplier–retailer supply chain with the presence of an outside market. Taking the local supplier's maximum production capacity and the outside market barriers into account, we identify the Pareto set of the push and/or pull contracts and draw managerial implications. The main results include the following. First, the most inefficient point of the pull Pareto set cannot always be removed by considering both the push and pull contracts. Second, the supplier's production capacity plays a significant role in the presence of an outside market; it affects the supplier's negotiating power with the retailer and the coordination of the supply chain can be accomplished only with a large enough capacity. Third, the import and export barriers influence the supply chain significantly: (i) an export barrier in the local market and the supplier's production capacity influence the supplier's export strategy; (ii) a low import (resp., export) barrier in the local market can improve the local supply chain's efficiency by use of a push (resp., pull) contract; and (iii) a high import (resp., export) barrier in the local market encourages the supplier (resp., retailer) to bear more inventory risk.     

Retailer's Response to Alternate Manufacturer's Incentives Under a Single‐Period,Price‐Dependent,Stochastic‐Demand Framework*

This article considers the joint development of the optimal pricing and ordering policies of a profit‐maximizing retailer, faced with (i) a manufacturer trade incentive in the form of a price discount for itself or a rebate directly to the end customer; (ii) a stochastic consumer demand dependent upon the magnitude of the selling price and of the trade incentive, that is contrasted with a riskless demand, which is the expected value of the stochastic demand; and (iii) a single‐period newsvendor‐type framework. Additional analysis includes the development of equal profit policies in either form of trade incentive, an assessment of the conditions under which a one‐dollar discount is more profitable than a one‐dollar rebate, and an evaluation of the impact upon the retailer‐expected profits of changes in either incentive or in the degree of demand uncertainty. A numerical example highlights the main features of the model. The analytical and numerical results clearly show that, as compared to the results for the riskless demand, dealing with uncertainty through a stochastic demand leads to (i) (lower) higher retail prices if additive (multiplicative) error, (ii) lower (higher) pass throughs if additive (multiplicative) error, (iii) higher claw backs in both error structures wherever applicable, and (iv) higher rebates to achieve equivalent profits in both error structures.     

Interorganizational Collaborative Forecasting and Replenishment Systems and Supply Chain Implications

Collaborative Forecasting and Replenishment (CFAR) is a new interorganizational system that enables retailers and manufacturers to forecast demand and schedule production jointly. The capabilities of CFAR exceed those of the traditional EDI because CFAR allows exchange of complex decision support models and manufacturer/retailer strategies. The proponents of CFAR claim that the fastest way for retailers and manufacturers to slash inventory costs and product shortages is by coordinating their decisions. The impact of CFAR on the supply chain using a model consisting of a manufacturer selling its product through two independent identical retailers is analyzed. The model assumes that the manufacturer doesn't face capacity constraints, the demand is stationary, and retailer prices are constant over time; the shortages are backordered at the manufacturer and retailers to isolate the effects of information sharing in CFAR. The most significant findings relate to the increase in the cost incurred by the nonparticipant in CFAR, the increase in the manufacturer's cost of serving the nonparticipant if the participant can obtain delivery guarantees in return for demand information sharing, and the incentives of the players to move towards universal retailer participation in CFAR. The findings are explained using the risk structure faced by the players in the supply chain. The managerial implications of the impact of CFAR on the supply chain structure are also discussed.     

Supply Chain Conflict Due to Store Brands: The Value of Wholesale Price Commitment in a Retail Supply Chain*

Store brands are of increasing importance in retail supply chains, often causing channel conflict, as the retailer's product directly competes with the manufacturer's national brand. Extant research on the resulting channel interactions either assumes the national brand manufacturer can credibly commit to maintaining a wholesale price or that he lacks such ability. However, these two scenarios imply very different supply chain interactions, as only a national brand manufacturer with commitment ability can strategically adjust a national brand wholesale price to prevent a store brand introduction by the retailer. We specifically analyze the impact of this assumption on the manufacturer, the retailer, and the customers. We determine when long‐term contracts that provide the manufacturer with such commitment ability can improve supply chain profitability.     

Supply Chain Management of Fresh Products with Producer Transportation*

This article considers a class of fresh‐product supply chains in which products need to be transported by the upstream producer from a production base to a distant retail market. Due to high perishablility a portion of the products being shipped may decay during transportation, and therefore, become unsaleable. We consider a supply chain consisting of a single producer and a single distributor, and investigate two commonly adopted business models: (i) In the “pull” model, the distributor places an order, then the producer determines the shipping quantity, taking into account potential product decay during transportation, and transports the products to the destination market of the distributor; (ii) In the “push” model, the producer ships a batch of products to a distant wholesale market, and then the distributor purchases and resells to end customers. By considering a price‐sensitive end‐customer demand, we investigate the optimal decisions for supply chain members, including order quantity, shipping quantity, and retail price. Our research shows that both the producer and distributor (and thus the supply chain) will perform better if the pull model is adopted. To improve the supply chain performance, we propose a fixed inventory‐plus factor (FIPF) strategy, in which the producer announces a pre‐determined inventory‐plus factor and the distributor compensates the producer for any surplus inventory that would otherwise be wasted. We show that this strategy is a Pareto improvement over the pull and push models for both parties. Finally, numerical experiments are conducted, which reveal some interesting managerial insights on the comparison between different business models.     

e‐Integration in the Supply Chain: Barriers and Performance*

Current opinion holds that Internet‐based supply chain integration with upstream suppliers and downstream customers (called “e‐integration” in this paper) is superior to traditional ways of doing business. This proposition remains untested, however, and similarly we know little about what are the upstream, internal, and downstream barriers to implementing e‐integration. This paper empirically addressed these questions using data from a large single nation study, and found (1) a positive link between e‐integration and performance, and (2) that internal barriers impeded e‐integration more than either upstream supplier barriers or downstream customer barriers. Findings from this study contribute to our theoretical understanding of implementing change in contemporary supply chains, and have important implications for manufacturers interested in improving their supply chain's performance using the Internet.     

The Impact of Forecast Errors on Early Order Commitment in a Supply Chain*

Supply chain partnership involves mutual commitments among participating firms. One example is early order commitment, wherein a retailer commits to purchase a fixed‐order quantity and delivery time from a supplier before the real need takes place. This paper explores the value of practicing early order commitment in the supply chain. We investigate the complex interactions between early order commitment and forecast errors by simulating a supply chain with one capacitated supplier and multiple retailers under demand uncertainty. We found that practicing early order commitment can generate significant savings in the supply chain, but the benefits are only valid within a range of order commitment periods. Different components of forecast errors have different cost implications to the supplier and the retailers. The presence of trend in the demand increases the total supply chain cost, but makes early order commitment more appealing. The more retailers sharing the same supplier, the more valuable for the supply chain to practice early order commitment. Except in cases where little capacity cushion is available, our findings are relatively consistent in the environments where cost structure, number of retailers, capacity utilization, and capacity policy are varied.     

Supply Chain Disruptions and the Role of Information Asymmetry

This research investigates how information asymmetry between the firm and its investors can influence supply chain disruptions. In such settings, these actors may be induced to take steps which exacerbate rather than ameliorate both the likelihood and impact of disruptions. By better understanding these mechanisms, managers and investors alike are better armed to avoid the costly consequences.     

Managing Supply Risk for Vertically Differentiated Co‐Products

The manufacturing complexity of many high‐tech products results in a substantial variation in the quality of the units produced. After manufacturing, the units are classified into vertically differentiated products. These products are typically obtained in uncontrollable fractions, leading to mismatches between their demand and supply. We focus on product stockouts due to the supply–demand mismatches. Existing literature suggests that when faced with product stockouts, firms should satisfy all unmet demand of a low‐end product by downgrading excess units of a high‐end product (downward substitution). However, this policy may be suboptimal if it is likely that low‐end customers will substitute with a higher quality product and pay the higher price (upward substitution). In this study, we investigate whether and how much downward substitution firms should perform. We also investigate whether and how much low‐end inventory firms should withhold to strategically divert some low‐end demand to the high‐end product. We first establish the existence of regions of co‐production technology and willingness of customers to substitute upward where firms adopt different substitution/withholding strategies. Then, we develop a managerial framework to determine the optimal selling strategy during the life cycle of technology products as profit margins shrink, manufacturing technology improves, and more capacity becomes available. Consistent trends exist for exogenous and endogenous prices.     

Simulation Analysis of a Manufacturing Supply Chain*

A supply chain is a series of manufacturing plants that transform raw material into finished product. A pipeline within a supply chain refers to the stream of information, material, components, and assemblies that are associated with a particular product. It is typical for manufacturing plants to put considerable effort to optimize the performance of a horizontal slice of a supply chain (such as coordination among parts that share a common resource). The need to optimize the performance of the vertical slice (the supply chain connecting raw material to finished product) by controlling the transmission of schedule instability and the resulting inventory fluctuation is often overlooked. A schedule is stable if actual production requirements for a given period do not change from the forecast production requirements. Stable production schedules are important when managing supply chains as they help control inventory fluctuation and inventory accumulation. Failure to control schedule instability results in high average inventory levels in the system. In this paper a simulation analysis of supply chain instability and inventory is conducted, and it is shown how supply chains can be analyzed for continuous improvement opportunities using simulation. The focus is on a stamping pipeline in an automobile supply chain based on operating data from General Motors (GM). It is shown that the techniques used in this paper are a useful tool for supply chain analysis.     

节点企业间界面关系与供应链绩效研究

本论文从节点企业及其相互关系的角度对供应链结构进行了科学定义,并将之作为解释变量,在界定供应链节点企业间界面关系测量维度的基础上,通过世界PC业竞争格局变化中三条代表性供应链结构特征的对比,分析了供应链竞争优势如何从供应链节点企业间的关系重塑中产生,并如何影响到供应链总体绩效水平。论文最后提出了有关供应链结构、竞争优势和战略以及绩效关系的分析框架。     

Health Care Supply Chain Design: Toward Linking the Development and Delivery of Care Globally*

This article is motivated by the gap between the growing demand and available supply of high‐quality, cost‐effective, and timely health care, a problem faced not only by developing and underdeveloped countries but also by developed countries. The significance of this problem is heightened when the economy is in recession. In an attempt to address the problem, in this article, first, we conceptualize care as a bundle of goods, services, and experiences—including diet and exercise, drugs, devices, invasive procedures, new biologics, travel and lodging, and payment and reimbursement. We then adopt a macro, end‐to‐end, supply chain–centric view of the health care sector to link the development of care with the delivery of care. This macro, supply chain–centric view sheds light on the interdependencies between key industries from the upstream to the downstream of the health care supply chain. We propose a framework, the 3A‐framework, that is founded on three constructs—affordability, access, and awareness—to inform the design of supply chain for the health care sector. We present an illustrative example of the framework toward designing the supply chain for implantable device–based care for cardiovascular diseases in developing countries. Specifically, the framework provides a lens for identifying an integrated system of continuous improvement and innovation initiatives relevant to bridging the gap between the demand and supply for high‐quality, cost‐effective, and timely care. Finally, we delineate directions of future research that are anchored in and follow from the developments documented in the article.     

The Impact of E‐Replenishment Strategy on Make‐to‐Order Supply Chain Performance

This research investigates the impact of electronic replenishment strategy on the operational activities and performance of a two‐stage make‐to‐order supply chain. We develop simulation‐based rolling schedule procedures that link the replenishment processes of the channel members and apply them in an experimental analysis to study manual, semi‐automated, and fully automated e‐replenishment strategies in decentralized and coordinated decision‐making supply chain structures. The average operational cost reductions for moving from a manual‐based system to a fully automated system are 19.6, 29.5, and 12.5%, respectively, for traditional decentralized, decentralized with information sharing, and coordinated supply chain structures. The savings are neither equally distributed among participants, nor consistent across supply chain structures. As expected, for the fully coordinated system, total costs monotonically decrease with higher levels of automation. However, for the two decentralized structures, under which most firms operate today, counter‐intuitive findings reveal that the unilateral application of e‐procurement technology by the buyer may lower his purchasing costs, but increase the seller's and system's costs. The exact nature of the relationship is determined by the channel's operational flexibility. Broader results indicate that while the potential economic benefit of e‐replenishment in a decentralized system is substantial, greater operational improvements maybe possible through supply chain coordination.     

Capacity Investment and Product Line Decisions of a Multiproduct Leader and a Focus Strategy Entrant

In this article, I investigate the capacity investment cost conditions where a multiproduct market leader may respond to a focus strategy entrant by using different strategies such as changing the product mix, production volumes, quality levels, and/or by investing in more capacity. The products offered in the market are quality differentiated and customers are heterogeneous in their willingness to pay for quality. The capacity investment costs of the two firms (i.e., the leader and the entrant) may also be different. The classical Stackelberg model predicts that an incumbent does not change its position in response to entry. However, when heterogeneous customer base, product differentiation, and capacity costs are taken into consideration, I find that the leader with a low capacity cost may choose to expand its product line and increase its production. The leader with low capacity cost may introduce a product that it was holding back when the entrant has to bear the high‐capacity cost and cannibalization threat is relatively small. Nevertheless, the extent of production volume strategies reduces as the capacity cost increases for the leader. I also find that when the leader has the power to set the industry standards by deciding the quality levels, as a response to a high‐quality focused entrant, the leader increases both levels of quality and production of the low‐quality product. Moreover, when the capacity investment cost is high for both the entrant and the leader, I find that market prices may increase with entry.     

Strategic Purchases of Bundled Products in a Health Care Supply Chain Environment*

Recent articles in the Wall Street Journal summarize the state of business practice in American hospitals by shedding light on the state of supply chain management practices and foci in today's health care supply chains. In health care, the single largest cost after labor is materials, and it has been documented that health care facilities can reduce the environmental impacts of the products and services they consume before regulatory problems arise or waste disposal costs increase by focusing on their upstream activities. Health care systems around the country consume significant quantities and varieties of products within the health delivery processes. Solving these environmental problems requires a much broader view involving collaborative efforts of professionals from different areas of health care to meet these challenges. The purchasing function bridges the gaps by providing a healthy dialogue on key environmental attributes within the health care supply chain. The concept of bundling new with refurbished products is gaining a lot of attention in the health care supply chain. This research describes a health care purchasing problem for bundling new and refurbished products of the type facing a growing number of large health care providers, and then proposes a methodology for evaluating the complex tradeoffs involved in bundling decisions for refurbished health care products. By exploiting some useful properties of the problem structure, our results provide buyers with useful insights for examining and selecting suppliers who are willing to offer bundles of new and refurbished products.     

Coordinating a Supply Chain When Facing Strategic Consumers

This article examines the impact of strategic consumers on the efficiency and coordination of a supply chain. We consider a supply chain consisting of a manufacturer and a newsvendor retailer selling a seasonal product to strategic consumers, who may choose to wait for clearance sales to maximize their intertemporal utility. Under a prenegotiated supply contract, the retailer chooses retail price and ordering quantity simultaneously. After that, the strategic consumers, who may be heterogeneous in their patience levels, make purchasing decisions. We find that strategic consumer behavior can hurt the supply chain efficiency due to severe double marginalization, and that a simple buyback contract can coordinate the supply chain. Nevertheless, we show that the supply chain does become more difficult to coordinate when strategic consumers are present: the set of buyback contractual terms that coordinate the chain shrinks as consumers are more willing to wait, and the chain profit cannot be arbitrarily allocated between the firms. Contrary to popular intuition, this result implies that the retailer may enjoy some benefit from consumers' strategic waiting. In addition, we find that the retailer's gain is the highest when impatient and patient consumers are comparably mixed in the population.      

Modeling Supply Chain Dynamics: A Multiagent Approach*

A global economy and increase in customer expectations in terms of cost and services have put a premium on effective supply chain reengineering. It is essential to perform risk-benefit analysis of reengineering alternatives before making a final decision. Simulation provides an effective pragmatic approach to detailed analysis and evaluation of supply chain design and management alternatives. However, the utility of this methodology is hampered by the time and effort required to develop models with sufficient fidelity to the actual supply chain of interest. In this paper, we describe a supply chain modeling framework designed to overcome this difficulty. Using our approach, supply chain models are composed from software components that represent types of supply chain agents (e.g., retailers, manufacturers, transporters), their constituent control elements (e.g., inventory policy), and their interaction protocols (e.g., message types). The underlying library of supply chain modeling components has been derived from analysis of several different supply chains. It provides a reusable base of domain-specific primitives that enables rapid development of customized decision support tools.     

Supply Chain Knowledge and Performance: A Meta‐Analysis

Many firms make significant investments into developing and managing knowledge within their supply chains. Such investments are often prudent because studies indicate that supply chain knowledge (SCK) has a positive influence on performance. Key questions still surround the SCK–performance relationship, however. First, what is the overall relationship between SCK and performance? Second, under what conditions is the relationship stronger or weaker? To address these questions, we applied meta‐analysis to 35 studies of the SCK–performance relationship that collectively include more than 8,400 firms. Our conservative estimate is that the effect size of the overall relationship is  = .39. We also find that the SCK–performance relationship is stronger when (i) examining operational performance, (ii) gathering data from more than one supply chain node, (iii) gathering data from multiple countries, (iv) examining service industries, and (v) among more recently published studies. We also found that studies that embraced a single theory base (as opposed to using multiple ones) had a stronger SCK–performance relationship. Looking to the future, our meta‐analysis highlights the need for studies to (i) include lags between the measurement of SCK and performance, (ii) gather upstream data when examining innovation, (iii) examine SCK within emerging countries, and (iv) provide much more information relative to the nuances of the SCK examined.