When Does a Retailer's Advance Selling Capability Benefit Manufacturer,Retailer, or Both?

Advance selling (AS) from a retailer to consumers is commonly observed in practice. With an AS capability, a retailer has the option to sell in advance or not. Having the AS option seems to increase flexibility and thus profit for a retailer. However, we show that the AS option can hurt the retailer's profit as well as supply chain performance. We identify two thresholds for a product's marginal production cost. A retailer's AS option benefits both the manufacturer and retailer when the marginal production cost is high, that is, above both thresholds. It benefits the manufacturer but hurts the retailer when the marginal production cost is moderate, that is, between the two thresholds. The result is ambiguous when the marginal production cost is low, that is, below both thresholds. We find that consumer valuation uncertainty under AS is the key driving force for the surprising result that having the retailer's AS option can hurt the retailer. When compared to the scenario where the retailer does not have the AS option, we find that the manufacturer's optimal wholesale price weakly decreases under the retailer's AS option if the marginal production cost is high. The statement is reversed if the marginal production cost is moderate or low.     

飞行频率、拥挤成本和互补型航空联盟:中枢轮辐网络机场拥挤分析

本文在基于飞行频率、拥挤成本和互补型航空联盟的基础上系统分析了中枢轮辐网络机场拥挤问题。研究表明:航空公司的利润最大化使得航班飞行频率存在过度供给,飞机大小也是次优的,这进一步恶化了中枢机场的机场拥挤;航班飞行频率与航空公司的拥挤成本系数、旅行计划延迟效用系数正相关,与飞机每次起降的固定成本负相关;互补型航空联盟使得联盟体利润增加,航空联盟对连接市场乘客有利,对本地市场乘客不利,航空联盟还可以内化伙伴间拥挤,航班飞行频率得以优化,机场拥挤得以缓解。     

Optimal procurement of long-term contracts in the presence of imperfect spot market

B2B spot market has grown rapidly and become an effective trading channel for commodity products. Besides long-term contract procurement from conventional suppliers (forward and option), a buyer can procure or sell commodities at any time in B2B spot market to adjust her inventory level. However, spot prices are generally volatile and the market is imperfect in the sense that spot trading may be realized with uncertainty in a given period of time and often comes with extra transaction cost. This paper considers a commodity buyer who can order forward and option contracts in advance and trade in a B2B spot market when spot price and demand are observed stochastically. Based on a single-period newsvendor model, we discuss three optimal order strategies and derive respective expected profits when the buyer is risk-neutral. The sensitivity of purchase costs, market liquidity and transaction cost is investigated. We also compare the optimal expected profits for different strategies to illustrate the effects of the two long-term contracts in the presence of the B2B spot market. We then extend our model to a multi-period setting and derive the optimal strategy. Finally, we numerically compute the optimal order strategy for a risk-averse buyer and analyze the impact of spot market, risk aversion, as well as the correlation between customer demand and spot price.     

Managing Risks in Multiple Online Auctions: An Options Approach*

The scenario of established business sellers utilizing online auction markets to reach consumers and sell new products is becoming increasingly common. We propose a class of risk management tools, loosely based on the concept of financial options that can be employed by such sellers. While conceptually similar to options in financial markets, we empirically demonstrate that option instruments within auction markets cannot be developed employing similar methodologies, because the fundamental tenets of extant option pricing models do not hold within online auction markets. We provide a framework to analyze the value proposition of options to potential sellers, option‐holder behavior implications on auction processes, and seller strategies to write and price options that maximize potential revenues. We then develop an approach that enables a seller to assess the demand for options under different option price and volume scenarios. We compare option prices derived from our approach with those derived from the Black‐Scholes model ( Black & Scholes, 1973 ) and discuss the implications of the price differences. Experiments based on actual auction data suggest that options can provide significant benefits under a variety of option‐holder behavioral patterns.     

Minimization of passenger takeoff and landing risk in offshore helicopter transportation: Models,approaches and analysis

Offshore petroleum industry uses helicopters to transport the employees to and from installations. Takeoff and landing represent a substantial part of the flight risks for passengers. In this paper, we propose and analyze approaches to create a safe flight schedule to perform pickup of employees by several independent flights. Two scenarios are considered. Under the non-split scenario, exactly one visit is allowed to each installation. Under the split scenario, the pickup demand of an installation can be split between several flights. Interesting links between our problem and other problems of combinatorial optimization, e.g., parallel machine scheduling and bin-packing are established. We provide worst-case analysis of the performance of some of our algorithms and report the results of computational experiments conducted on randomly generated instances based on the real sets of installations in the oil fields on the Norwegian continental shelf. This paper is the first attempt to handle takeoff and landing risk in a flight schedule that consists of several flights and lays ground for the study on more advanced and practically relevant models.     

Solving the flight gate assignment problem using dynamic programming

This paper considers the problem of assigning flights to airport gates—a problem which is NP-hard in general. We focus on a special case in which the maximization of flight/gate preference scores is the only objective. We show that for a variable number of flights and gates, this problem is still NP-hard. For a fixed number of gates, we present a dynamic programming approach that solves the flight assignment problem in linear time with respect to the number of flights. Computational results using real life data from a major European airport prove the practical relevance of this approach.     

Balancing Inventory and Stockout Risk in Retail Supply Chains Using Fast‐Ship

In this study, we consider a two‐retailer, one‐supplier supply chain in which retailers satisfy excess demand by offering to directly ship out‐of‐stock items on an expedited basis at no extra cost to customers. This practice is referred to as the fast‐ship option. We consider two scenarios along with the fast‐ship option. In the first scenario, retailers transship when out of stock, whereas in the second scenario, they do not. If they do not transship, some customers may perform the search on their own. In each scenario, the wholesale prices are either exogenous, or chosen endogenously by the supplier. For both cases, we determine the supplier's and the retailers’ optimal decisions. The key research question we ask and answer is the following: which of the two scenarios is preferred by either player when all decisions are made optimally? We show that when fewer customers are willing to search on their own and wholesale prices are exogenous, both the supplier and the retailers prefer to transship. In addition, the decision maker in a centralized chain will have the exact same preference as that of players in a decentralized setting when the retailers’ and the supplier's preferences coincide and wholesale prices are exogenous. This preference concordance does not hold if wholesale prices are endogenous.     

A real options model of market entry: Endogenous uncertainty and exogenous uncertainty

We develop a real options model of market entry that focuses on the dueling growth and deferral options by differentiating between endogenous uncertainty and exogenous uncertainty. While exogenous uncertainty influences the growth option market value or price, it is endogenous uncertainty that influences the value of the growth option through the ability to create a competitive advantage from preemptive market entry. First, the firm can decrease the exercise price of the growth option (i.e., the cost of the follow-on investment) through experiential learning that reduces endogenous uncertainty. Second, the firm can increase the relative discounted cash flows of the follow-on investment due to its ability to influence market demand that reduces endogenous uncertainty. On the other hand, the value of the deferral option increases with exogenous uncertainty as firms cannot influence exogenous uncertainty, and therefore, should invest elsewhere while waiting for the exogenous uncertainty to subside. As such, we provide a solution to the conundrum that the value of both the growth option and the deferral option increase with uncertainty. Finally, we demonstrate how the model addresses sequential market entry; irreversibility and market entry mode; competition; scarce strategic resources; host country development level; and industry life cycle stage.     

基于二重随机因素的对称双头垄断期权博弈模型

本文在产品市场需求与经营成本二重随机性以及二者具有相关性的条件下,建立了一个对称双头垄断期权博弈分析框架,研究了企业最优战略投资决策问题。在导出企业投资价值函数和最优投资临界值的基础上,着重分析了企业最优投资策略均衡规则及各均衡存在的条件,并就各参数对企业最优投资临界值的影响进行比较静态分析,得出了一些有意义的结论,同时给出了经济解释。     

Portfolio-based airline fleet planning under stochastic demand

Airlines operate their fleet of aircraft over a relatively long time horizon during which the realized stochastic demand has the potential to profoundly impact the airlines’ financial performance. This makes the investment in a fleet of aircraft a highly capital-intensive long-term commitment, associated with inherent risks. We propose an innovative three-step airline fleet planning methodology with the primary objective of identifying fleets that are robust to stochastic demand realizations. The methodology presents two main innovation aspects. The first one is the use of the mean reverting Ornstein–Uhlenbeck process to model the long-term travel demand, which is then combined with discrete-time Markov chain transitions to generate demand scenarios. The second innovative aspect is the adoption of a portfolio-based fleet planning perspective that allows for an explicit comparison of different fleets, in size and composition. Ultimately, the methodology yields for each fleet in the portfolio a distribution of net present values of operating profit across the planning horizon and a list of key financial and operational metrics per year. The robustest fleet can be selected based on the operating profit generating capability across different realizations of stochastic demand. An illustrative case study is presented as a proof of concept. The case study is used to demonstrate the type of results obtained and to discuss the usefulness of the methodology proposed.     

A Note on Air‐Cargo Capacity Contracts

Carriers (airlines) use medium‐term contracts to allot bulk cargo capacity to forwarders who deliver consolidated loads for each flight in the contractual period (season). Carriers also sell capacity to direct‐ship customers on each flight. We study capacity contracts between a carrier and a forwarder when certain parameters such as the forwarder's demand, operating cost to the carrier, margin, and reservation profit are its private information. We propose contracts in which the forwarder pays a lump sum in exchange for a guaranteed capacity allotment and receives a refund for each unit of unused capacity according to a pre‐announced refund rate. We obtain an upper bound on the informational rent paid by the carrier for a menu of arbitrary allotments and identify conditions under which it can eliminate the informational rent and induce the forwarder to choose the overall optimal capacity allotment (i.e., one that maximizes the combined profits of the carrier and the forwarder).     

A Learning Real Options Framework with Application to Process Design and Capacity Planning

This paper studies the impact of learning on a multi‐staged investment scenario. In contrast to other models in the real options literature in which learning is viewed as a passive consequence of the delay period, this paper quantifies information acquisition by merging statistical decision theory with the real options framework. In this context, real option attributes are discussed from a Bayesian perspective, thresholds are identified for improved decision‐making, and information's impact on downstream decision‐making is discussed. Using real data provided by a firm in the aerospace maintenance, repair, and overhaul industry, the methodology is used to guide a multi‐phased irreversible investment decision involving process design and capacity planning.     

Heuristic approaches for flight retiming in an integrated airline scheduling problem of a regional carrier

Flight retiming in airline scheduling consists in slightly modifying the scheduled departure time of some flights with the goal of providing a better service with a cheaper cost. In this research, the departure times must be selected from a small discrete set of options. The whole problem embeds flight retiming, fleet assignment, aircraft routing and crew pairing. Thus, the aim is to determine the departure times of the flights, the fleet assignment and the minimum cost aircraft and crew routes. The objective function takes into account a large cost associated with each crew member, a penalization for short or long connection times, a cost for crew members changing aircraft along their routes, and a minor penalty associated with the use of each aircraft. The constraints enforce aircraft maintenance and crew working rules. In this setting, flight retiming is allowed to potentially reduce the total costs and increase the robustness of the solution against delays by decreasing the number of aircraft changes.We propose and compare four heuristic algorithms based on a Mixed Integer Linear Programming model for the whole problem. The model contains path variables representing the crew pairings, and arc variables representing the aircraft routes. In the heuristic algorithms, column generation is applied on the path variables, and different flight retiming options are considered. The algorithms are tested on real-world instances of a regional carrier flying in the Canary Islands to evaluate their advantages and drawbacks. In particular, one of the algorithms, that uses the solution of the Linear Programming relaxation of the model to select promising options for the departure of the flights, turns out to be the most effective one. The obtained results show that costs can be significantly reduced through flight retiming while still keeping the computing times reasonably short. In addition, we perform a sensitivity analysis by including more retiming options and by using different aircraft and crew costs. Finally, we report the results on larger size instances obtained by combining real-world ones.     

基于ASRank和MMAS的蚁群算法求解飞机指派问题

本文将航班串的飞机指派问题归结为车辆路径问题,考虑连续航班串之间衔接时间、衔接机场的约束、每架飞机的总飞行时间约束,建立了带有飞行时间约束的车辆路径问题的混合整数规划模型。构造了蚁群系统算法,引入基于排序的蚂蚁系统和最大最小蚂蚁系统算法的信息素更新策略。选取某航空公司7组初始航班串集合进行测试,并对算法中的重要参数进行了分析。实验结果表明,本文设计的模型和算法可以有效地减少连续航班串之间的总衔接时间,在可接受的计算时间内获得满意解。     

The Newsvendor Model with Consumer Search Costs

We study the newsvendor problem when consumers are heterogeneous either in their valuations of the newsvendor's product, in their valuations of an outside option available to them, or in both valuations. In this context, we observe that the outside option, which represents the value that a given consumer associates with choosing not to purchase the newsvendor's product, may be interpreted as a search cost. Taking into consideration whether consumers' valuations differ on either one dimension of heterogeneity or on both dimensions, we develop a framework for classifying newsvendor models that incorporate demand‐management effects. In particular, we show that this framework includes both the newsvendor model with price‐dependent demand and the newsvendor model with endogenous demand as special cases. In addition to making a conceptual contribution by developing and drawing insights from this framework, we make technical contributions by providing more general sufficient conditions under which the underlying optimization problems are well behaved.     

In-house capability and supply chain decisions

This study considers an internal production option for a contractor and analyzes its effect on the supply chain decisions when the contractor has innovated and the subcontractor has an incentive for opportunistic behavior. In contrast to the single disclosure threshold in the benchmark scenario where the contractor lacks in-house capability, we find two thresholds in the referred scenario. When information misappropriation is possible and the contractor has in-house capability, the contractor will organize a coordinated supply chain only when innovations fall between the two thresholds. Compared to the benchmark scenario, in-house capability has a positive effect on the contractor's incentive to innovate and an ambiguous effect on the subcontractor's incentive to invest in the production process. When the contractor needs to incur an extra cost to build in-house capability, the contractor keeps the same levels of investment compared to the case of no additional in-house capability cost, whereas the subcontractor increases the levels of investment. Furthermore, we find that in the presence of potential misappropriation on the part of the subcontractor, the higher the level of in-house capability, the less likely the contractor will be to outsource innovative products that generate higher profitability. This study can explain why firms strategically outsource low-end products and produce high-end products themselves. This study provides new results on the effects of in-house capability on the strategic interactions of parties in supply chains and, hence, on supply chain efficiency.     

Reducing Packaging Waste and Cost via Consumer Price Discounts

Low‐waste packaging may imply an inconvenience to consumers and cause firms to offer a compensating price discount. For example, Starbucks’ “Take the Mug Pledge” campaign provides a 10‐cent discount for customers who purchase coffee without a standard cup (i.e., customers provide their own cup). Understanding how such a discount drives demand and profit is the focus of this article. We consider a monopolist that can offer a reduced‐packaging option for its product at a variable cost savings. That option implies a transactional “inconvenience” cost for consumers. While that transactional cost is generally positive, our model also permits some consumers to associate convenience with reduced packaging. We derive the optimal price and discount that maximize profits. We show the optimal discount is bounded by the magnitude of the variable cost savings associated with the packaging reduction. We explore when the optimal discount is negative (a price premium), which requires a specific proportion of consumers to associate convenience with reduced packaging. We also derive conditions under which the firm should price to eliminate demand for the standard product, rather than segment the market, to leverage the variable cost savings of reduced packaging. When the variable cost savings are low (e.g., as is true for Starbucks), we show the profit curve for the segmenting policy is relatively flat for a discount up to several multiples of the cost differential. Finally, we demonstrate the potential for the reduced packaging option, with optimal discounting, to simultaneously increase profit and consumer surplus while reducing waste.     

Combined Pricing and Portfolio Option Procurement

In this paper, we study a single‐product periodic‐review inventory system that faces random and price‐dependent demand. The firm can purchase the product either from option contracts or from the spot market. Different option contracts are offered by a set of suppliers with a two‐part fee structure: a unit reservation cost and a unit exercising cost. The spot market price is random and its realization may affect the subsequent option contract prices. The firm decides the reservation quantity from each supplier and the product selling price at the beginning of each period and the number of options to exercise (inventory replenishment) at the end of the period to maximize the total expected profit over its planning horizon. We show that the optimal inventory replenishment policy is order‐up‐to type with a sequence of decreasing thresholds. We also investigate the optimal option‐reservation policy and the optimal pricing strategy. The optimal reservation quantities and selling price are shown to be both decreasing in the starting inventory level when demand function is additive. Building upon the analytical results, we conduct a numerical study to unveil additional managerial insights. Among other things, we quantify the values of the option contracts and dynamic pricing to the firm and show that they are more significant when the market demand becomes more volatile.     

Advertising in Asymmetric Competing Supply Chains

Advertising is a crucial tool for demand creation and market expansion. When a manufacturer uses a retailer as a channel for reaching end customers, the advertising strategy takes on an additional dimension: which party will perform the advertising to end customers. Cost sharing (“co‐operative advertising”) arrangements proliferate the option by decoupling the execution of the advertising from its funding. We examine the efficacy of cost sharing in a model of two competing manufacturer–retailer supply chains who sell partially substitutable products that may differ in market size. Some counterintuitive findings suggest that the firms performing the advertising would rather bear the costs entirely if this protects their unit profit margin. We also evaluate the implications of advertising strategy for overall supply chain efficiency and consumer welfare.     

期权动态套期保值双相机决策模型及实证研究

金融市场具有多变性,投资者一般需要根据市场情况动态地改变套期保值策略,使套期保值组合价格波动的风险被对冲掉。因此,有必要建立期权动态套期保值模型,得到动态的最优期权头寸,这意味着投资者需要按照模型所得到的头寸动态调仓才能达到风险最小的目的。然而,买入期权进行套期保值需要支付期权金成本,也就是投资者为了达到风险最小化的目的需要付出成本代价。那么,付出的代价是否“划算”是投资者面临的一个问题。此外,买入欧式看跌期权可以规避现货价格下跌的风险,但欧式期权只有到到期日时才能被执行,而投资者不一定要持有期权直到到期日。于是,投资者在投资期间选择何时退出是期权动态套期保值的另一个问题。 针对传统的期权套期保值策略存在错失退出良机和调仓过于频繁的问题,提出退出和调仓双相机决策准则,进一步优化传统套期保值策略。在满足预算、预期收益、头寸约束条件下,建立基于在险价值的最优期权动态套期保值模型,得到传统动态套期保值策略。在此基础上,基于经济价值视角将风险和成本代价统一化度量,利用期末绩效评价提出退出和调仓双相机决策准则,进一步修正期权套期保值策略。利用上证50ETF及以上证50ETF为标的的期权开展实证研究。 研究结果表明,运用退出相机准则提供了提前退出投资的参考时间点,运用调仓相机准则通过减少不必要的调仓降低调仓成本。通过对比发现传统的期权动态套期保值策略存在缺陷,运用双相机抉择的期权套期保值策略能够获得更有效率的套期保值结果。利用退出相机提供7个参考退出交易日,若在这些交易日选择退出,投资者将获得比较大的利润,利用调仓相机后增加了收益。 考虑双相机决策的期权最优套期保值模型改进了传统模型的单一决策,提出了更有效的风险控制策略,为投资者提供决策参考具有实际意义。