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ABSTRACTWe examine the strategic interplay between a buyer's design decision and the ensuing competition between suppliers in a three‐tier closed‐loop supply chain setting with significant recycling considerations. The nature of the engineering design decision in our research entails choice of integral versus modular design that has direct implications for the input raw material waste and ensuing competition between suppliers (i.e., incumbent and new). Whereas the integral design requires a large blank and generates excessive material scrap, the modular design reduces the generated scrap, and enhances cut‐to‐fit modularity, but incurs joining cost and yield loss. The incumbent supplier who supports the status quo choice of integral design can effectively recycle excessive material waste, as it is strategically located close to the source of material. The engineering design team at our study firm is currently exploring the option to source from alternative suppliers that can support either integral or modular designs, but have significantly lower effectiveness in recycling scrap material. We characterize the buyer's price sensitivity levels, component characteristics, supply chain configurations, and virgin and scrap specialty material prices that yield various design and sourcing policy alternatives. The buyer's optimal policy choice, the ensuing price–demand dynamics, and the resulting recycling implications demonstrate that the buyer can benefit from strategically tailoring his design decisions to affect the suppliers' material requirements and costs. We show that utilizing an alternative supply option is particularly valuable for components made from a material with a low price differential in virgin and scrap forms in supply chains wherein the new supplier base can recycle effectively. In such cases, the buyer induces severe price competition by dual sourcing the integral design, and competition may negate the seemingly obvious benefits of operational improvements (e.g., higher scrap material return rate).

ABSTRACTThe Internet is providing an opportunity to revenue management practitioners to exploit the potential of auctions as a new price distribution channel. We develop a stochastic model for a high‐level abstraction of a revenue management system (RMS) that allows us to understand the potential of incorporating auctions in revenue management in the presence of forecast errors associated with key parameters. Our abstraction is for an environment where two market segments book in sequence and revenue management approaches consider auctions in none, one, or both segments. Key insights from our robust results are (i) limited auctions are best employed closest to the final sale date, (ii) counterbalancing forecast errors associated with overall traffic intensity and the proportion of customer arrivals in a segment is more important if an auction is adopted in that segment, and (iii) it is critically important not to err on the side of overestimating market willingness to pay.

ABSTRACTWe develop a stochastic model to explore the benefits of incorporating auctions in revenue management. To the best of our knowledge the extant literature on modeling in revenue management has not considered auctions. We consider three models, namely, a traditional fixed price (non‐auction) model, a pure auction model, and a hybrid auction model and evaluate their revenue performance under a variety of conditions. The hybrid approach outperforms the other two in all 24 scenarios and yields an average revenue increase of 16.1% over the next best. A surprise finding is that there is no significant difference between the performance of the fixed price and pure auction approaches. A sensitivity analysis reveals that the relative superiority of the hybrid revenue management strategy is reasonably robust.

AbstractWe analyze strategic relationships between buyers and sellers in markets with switching costs and dynamic uncertainty by investigating the scenario wherein a representative buyer trades with two foreign sellers located in the same foreign country. We show that, under exchange rate uncertainty, switching costs may lead to switching equilibria where both sellers co‐exist in the market with the buyer, or no‐switching equilibria where either seller captures the market. The presence of exchange rate uncertainty facilitates competition by allowing the sellers to co‐exist in the market with the buyer. However, if the level of uncertainty is beyond a threshold, the only viable equilibria are those where one of the sellers captures the market. Further, depending on the level of exchange rate uncertainty and the sellers' variable costs, switching costs may either raise or lower the level of prices in long‐term contracts between the buyer and the sellers. © 2007 Wiley Periodicals, Inc. Naval Research Logistics, 2007

ABSTRACTThis paper provides a fundamental building block to facilitate sourcing and allocation decisions for make‐to‐order items. We specifically address the buyer's vendor selection problem for make‐to‐order items where the goal is to minimize sourcing and purchasing costs in the presence of fixed costs, shared capacity constraints, and volume‐based discounts for bundles of items. The potential suppliers for make‐to‐order items provide quotes in the form of single sealed bids or participate in a dynamic auction involving open bids. A solution to our problem can be used to determine winning bids amongst the single sealed bids or winners at each stage of a dynamic auction. Due to the computational complexity of this problem, we develop a heuristic procedure based on Lagrangian relaxation technique to solve the problem. The computational results show that the procedure is effective under a variety of scenarios. The average gap across 2,250 problem instances is 4.65%.

ABSTRACTRevenue Management Systems (RMS) are commonly used in the hotel industry to maximize revenues in the short term. The forecasting‐allocation module is a key tactical component of a hotel RMS. Forecasting involves estimating demand for service packages across all stayover nights in a planning horizon. A service package is a unique combination of physical room, amenities, room price, and advance purchase restrictions. Allocation involves parsing the room inventory among these service packages to maximize revenues. Previous research and existing revenue management systems assume the demand for a service package to be independent of which service packages are available for sale. We develop a new forecasting‐allocation approach that explicitly accounts for this dependence. We compare the performance of the new approach against a baseline approach using a realistic hotel RMS simulation. The baseline approach reflects previous research and existing industry practice. The new approach produces an average revenue increase of at least 16% across scenarios that reflect existing industry conditions.

PurposeTo gain understanding of value chain (VC) agility in terms of value‐adding processes, this paper seeks to present a VC agility framework and then to develop the involved constructs.Design/methodology/approachA framework of VC agility and its theoretical underpinnings is presented. Within the framework, drivers and determinants of VC agility are identified as characteristics enabling flexibility within key components of a firm's VC. Also, it is posited that information technology (IT) capability impacts the levels of achieved flexibility and agility, and that VC agility impacts business performance.FindingsFrom scale development, key determinants of flexibility within VC activities are identified. Correlation analysis suggests that firms derive higher levels of agility through integrating information across the VC rather than within VC activities. Firms with flexibility in their VC functions enjoy higher levels of ensuing VC agility and on‐time delivery, ROA, and market share.Research limitations/implicationsWhile the sample size is adequate for scale development, it is not adequate for structural equation modeling since the guideline is to have at least five survey responses for every item measure. Thus, insights were gleaned from initial analysis based on correlations.Practical implicationsManagerial insights concerning key value‐adding activities that build flexibility and ultimately agility are identified.Originality/valueTo the best of one's knowledge, this work is the first to operationalize VC agility from the perspective that agility is derived from flexibility in the VC processes and is enabled by IT integration. From exploratory research, insights are gained on how VC agility links with business performance.