Quick Response under Competition

We consider a manufacturer serving two competing retailers that sell their products over a single selling season. The retailers place their regular orders before the season starts. In addition to this initial order, quick response (QR) provides a retailer with an additional replenishment opportunity after demand uncertainty is resolved. The manufacturer determines the unit price for QR replenishment. We characterize the retailers’ ordering, and the manufacturer's pricing decisions in equilibrium when none, only one, and both of the retailers have QR ability. We study how the profitability of the manufacturer, the retailers, and the channel depend on QR and competition. We find it may be optimal for the manufacturer to offer QR to only one of the ex ante identical retailers when demand variability is sufficiently, but not overly high. The manufacturer may also find it optimal to offer QR to both or none of the retailers, depending on demand variability. Finally, while QR ability is always attractive for a retailer when competition is ignored, we find QR may prove detrimental when its impact on competition is taken into account.     

Guidelines for Use of the Approximate Beta‐Poisson Dose–Response Model

For dose–response analysis in quantitative microbial risk assessment (QMRA), the exact beta‐Poisson model is a two‐parameter mechanistic dose–response model with parameters and , which involves the Kummer confluent hypergeometric function. Evaluation of a hypergeometric function is a computational challenge. Denoting as the probability of infection at a given mean dose d, the widely used dose–response model is an approximate formula for the exact beta‐Poisson model. Notwithstanding the required conditions and , issues related to the validity and approximation accuracy of this approximate formula have remained largely ignored in practice, partly because these conditions are too general to provide clear guidance. Consequently, this study proposes a probability measure Pr(0 < r < 1 | , ) as a validity measure (r is a random variable that follows a gamma distribution; and are the maximum likelihood estimates of α and β in the approximate model); and the constraint conditions for as a rule of thumb to ensure an accurate approximation (e.g., Pr(0 < r < 1 | , ) >0.99) . This validity measure and rule of thumb were validated by application to all the completed beta‐Poisson models (related to 85 data sets) from the QMRA community portal (QMRA Wiki). The results showed that the higher the probability Pr(0 < r < 1 | , ), the better the approximation. The results further showed that, among the total 85 models examined, 68 models were identified as valid approximate model applications, which all had a near perfect match to the corresponding exact beta‐Poisson model dose–response curve.     

The Effect of Demand–Supply Mismatches on Firm Risk

A supply chain management (SCM) system comprises many subsystems, including forecasting, order management, supplier management, procurement, production planning and control, warehousing and distribution, and product development. Demand–supply mismatches (DSMs) could indicate that some or all of these subsystems are not working as expected, creating uncertainties about the overall capabilities and effectiveness of the SCM system, which can increase firm risk. This article documents the effect of DSMs on firm risk as measured by equity volatility. Our sample consists of three different types of DSMs announced by publicly traded firms: production disruptions, excess inventory, and product introduction delays. We find that all three types of DSMs result in equity volatility increases. Over a 2‐year period around the announcement date, we observe mean abnormal equity volatility increases of 5.62% for production disruptions, 11.19% for excess inventory, and 6.28% for product introduction delays. Volatility increases associated with excess inventory are significantly higher than the increases associated with production disruptions and product introduction delays. Across all three types of DSMs, volatility changes are positively correlated with changes in information asymmetry. The results provide some support that volatility changes are also correlated with changes in financial and operating leverage.     

The Effect of Competition on Recovery Strategies

Manufacturers often face a choice of whether to recover the value in their end‐of‐life products through remanufacturing. In many cases, firms choose not to remanufacture, as they are (rightly) concerned that the remanufactured product will cannibalize sales of the higher‐margin new product. However, such a strategy may backfire for manufacturers operating in industries where their end‐of‐life products (cell phones, tires, computers, automotive parts, etc.) are attractive to third‐party remanufacturers, who may seriously cannibalize sales of the original manufacturer. In this paper, we develop models to support a manufacturer's recovery strategy in the face of a competitive threat on the remanufactured product market. We first analyze the competition between new and remanufactured products produced by a monopolist manufacturer and identify conditions under which the firm would choose not to remanufacture its products. We then characterize the potential profit loss due to external remanufacturing competition and analyze two entry‐deterrent strategies: remanufacturing and preemptive collection. We find that a firm may choose to remanufacture or preemptively collect its used products to deter entry, even when the firm would not have chosen to do so under a pure monopoly environment. Finally, we discuss conditions under which each strategy is more beneficial.     

Estimation of the Likelihood of Fecal–Oral HEV Transmission Among Pigs

Sources for human hepatitis E virus (HEV) infections of genotype 3 are largely unknown. Pigs are potential animal reservoirs for HEV. Intervention at pig farms may be desired when pigs are confirmed as a source for human infections, requiring knowledge about transmission routes. These routes are currently understudied. The current study aims to quantify the likelihood of pig feces in causing new HEV infections in pigs due to oral ingestion. We estimated the daily infection risk for pigs by modeling the fate of HEV in the fecal–oral (F–O) pathway. Using parameter values deemed most plausible by the authors based on current knowledge the daily risk of infection was 0.85 (95% interval: 0.03–1). The associated expected number of new infections per day was ～4 (2.5% limit 0.1, the 97% limit tending to infinity) compared to 0.7 observed in a transmission experiment with pigs, and the likelihood of feces causing the transmission approached 1. In alternative scenarios, F–O transmission of HEV was also very likely to cause new infections. By reducing the total value of all explanatory variables by 2 orders of magnitude, the expected numbers of newly infected pigs approached the observed number. The likelihood of F–O transmission decreased by decreasing parameter values, allowing for at most 94% of infections being caused by additional transmission routes. Nevertheless, in all scenarios F–O transmission was estimated to contribute to HEV transmission. Thus, despite the difficulty in infecting pigs with HEV via oral inoculation, the F–O route is likely to cause HEV transmission among pigs.     

股权融资下企业市场竞争策略选择的模型研究

企业市场竞争策略的制定不仅应考虑竞争双方运营层面的因素,还应重视其资本运作带来的影响。本文构建了零售商采取股权融资进行市场开拓的市场竞争模型,探讨其市场竞争策略选择及其影响因素。研究发现：零售商的市场竞争策略取决于其成长性和市场开拓的外部性;提高成长性或外部性均能促进企业的股权融资,而企业原股东的委托代理行为会抑制股权融资,并影响其市场开拓决策,但不会定性改变企业的价格竞争策略。此外,当市场开拓呈现负外部性时,竞争者应采取相应措施以避免掉入“融资企业成长性陷阱”。     

The Effect of Competition on R&D Portfolio Investments

Although project portfolio management has been an active research area over the past 50 years, budget allocation models that consider competition are sparse. Faced with the competition, firms contemplating budget allocation for their project portfolio cannot limit their attention to the returns from their projects' target markets, as is the case for monopoly firms, but must also anticipate the competitive effects on these returns. Assuming firms allocate their budgets between projects offering incremental innovation targeting a mature market and projects offering radical innovation targeting an emerging market, we show that while the monopoly firm bases its budget allocation decision solely on the marginal returns of the markets, competing firms—as they take into account their counterparts' investment decisions—need to also consider the projects' average returns from their respective markets. This drives competing firms into incrementalism: faced with competition, firms invest larger portions of their budgets into projects targeting mature markets. This effect is amplified as the number of competing firms increases and firms allocate an even greater share of their budget into projects targeting a mature market. We further demonstrate the effects that changes to firms' individual budgets, as well as to market characteristics, have on firms' budget allocation decision.     

Dose–Response Modeling: Extrapolating From Experimental Data to Real‐World Populations

Dose–response modeling of biological agents has traditionally focused on describing laboratory‐derived experimental data. Limited consideration has been given to understanding those factors that are controlled in a laboratory, but are likely to occur in real‐world scenarios. In this study, a probabilistic framework is developed that extends Brookmeyer's competing‐risks dose–response model to allow for variation in factors such as dose‐dispersion, dose‐deposition, and other within‐host parameters. With data sets drawn from dose–response experiments of inhalational anthrax, plague, and tularemia, we illustrate how for certain cases, there is the potential for overestimation of infection numbers arising from models that consider only the experimental data in isolation.     

A Bias–Reduced Log–Periodogram Regression Estimator for the Long–Memory Parameter

In this paper, we propose a simple bias–reduced log–periodogram regression estimator, ^d_r, of the long–memory parameter, d, that eliminates the first– and higher–order biases of the Geweke and Porter–Hudak (1983) (GPH) estimator. The bias–reduced estimator is the same as the GPH estimator except that one includes frequencies to the power 2k for k=1,…,r, for some positive integer r, as additional regressors in the pseudo–regression model that yields the GPH estimator. The reduction in bias is obtained using assumptions on the spectrum only in a neighborhood of the zero frequency. Following the work of Robinson (1995b) and Hurvich, Deo, and Brodsky (1998), we establish the asymptotic bias, variance, and mean–squared error (MSE) of ^d_r, determine the asymptotic MSE optimal choice of the number of frequencies, m, to include in the regression, and establish the asymptotic normality of ^d_r. These results show that the bias of ^d_r goes to zero at a faster rate than that of the GPH estimator when the normalized spectrum at zero is sufficiently smooth, but that its variance only is increased by a multiplicative constant. We show that the bias–reduced estimator ^d_r attains the optimal rate of convergence for a class of spectral densities that includes those that are smooth of order s≥1 at zero when r≥(s−2)/2 and m is chosen appropriately. For s>2, the GPH estimator does not attain this rate. The proof uses results of Giraitis, Robinson, and Samarov (1997). We specify a data–dependent plug–in method for selecting the number of frequencies m to minimize asymptotic MSE for a given value of r. Some Monte Carlo simulation results for stationary Gaussian ARFIMA (1, d, 1) and (2, d, 0) models show that the bias–reduced estimators perform well relative to the standard log–periodogram regression estimator.     

The institutionalization of knowledge transfer activities within industry–university collaborative ventures

Due to the changing competitive landscape, organizations must increasingly focus on acquiring external knowledge to advance new technologies. This study examines the institutionalization of knowledge transfer activities between industrial firms and university research centers. Data were collected from 189 firms collaborating with 21 university research centers in the US. Results show that knowledge transfer activities are facilitated when industrial firms have more mechanistic structures, cultures that are more stable and direction-oriented, and when the firm is more trusting of its university research center partner. Implications for both industry and universities, including their effect on firm performance, are discussed.     

Discrete–Time Approximations of the Holmström–Milgrom Brownian–Motion Model of Intertemporal Incentive Provision

This paper studies the relation between discrete–time and continuous–time principal–agent models. We derive the continuous–time model as a limit of discrete–time models with ever shorter periods and show that optimal incentive schemes in the discrete–time models approximate the optimal incentive scheme in the continuous model, which is linear in accounts. Under the additional assumption that the principal observes only cumulative total profits at the end and the agent can destroy profits unnoticed, an incentive scheme that is linear in total profits is shown to be approximately optimal in the discrete–time model when the length of the period is small.     

零售商导入自有品牌对渠道竞争的影响研究

为了增强谈判力量和提升自身的独特竞争优势,零售商开始提供自有品牌,而自有品牌的引入强化渠道成员间的竞争。本文将针对两个对称性制造商和单个零售商的渠道结构,探讨自有品牌导入对渠道竞争决策产生的影响。研究结果表明:在任何渠道权力结构下,自有品牌的导入会降低制造商品牌的利润;在制造商领导权和垂直纳什结构下,被模仿制造商品牌的利润下降更显著;而在零售商领导权结构下,未被模仿制造商品牌的利润下降更显著;在未导入自有品牌情况下,制造商处于领导权地位能提升零售商利润水平;而零售商导入自有品牌时,其结果则相反,制造商处于领导权地位会降低零售商的利润水平;在零售商领导权和垂直纳什结构下,导入自有品牌都能增加零售商利润;而在制造商领导权结构下,仅当制造商之间竞争程度较弱时,导入自有品牌能提高零售商利润。     

On the Discrete Version of the Aumann–Shapley Cost‐Sharing Method

Each agent in a finite set requests an integer quantity of an idiosyncratic good; the resulting total cost must be shared among the participating agents. The Aumann–Shapley prices are given by the Shapley value of the game where each unit of each good is regarded as a distinct player. The Aumann–Shapley cost‐sharing method charges to an agent the sum of the prices attached to the units she consumes. We show that this method is characterized by the two standard axioms of Additivity and Dummy, and the property of No Merging or Splitting: agents never find it profitable to split or to merge their consumptions. We offer a variant of this result using the No Reshuffling condition: the total cost share paid by a group of agents who consume perfectly substitutable goods depends only on their aggregate consumption. We extend this characterization to the case where agents are allowed to consume bundles of goods.     

Statistical Approach to Identify Threshold and Point of Departure in Dose–Response Data

The study presents an integrated, rigorous statistical approach to define the likelihood of a threshold and point of departure (POD) based on dose–response data using nested family of bent‐hyperbola models. The family includes four models: the full bent‐hyperbola model, which allows for transition between two linear regiments with various levels of smoothness; a bent‐hyperbola model reduced to a spline model, where the transition is fixed to a knot; a bent‐hyperbola model with a restricted negative asymptote slope of zero, named hockey‐stick with arc (HS‐Arc); and spline model reduced further to a hockey‐stick type model (HS), where the first linear segment has a slope of zero. A likelihood‐ratio test is used to discriminate between the models and determine if the more flexible versions of the model provide better or significantly better fit than a hockey‐stick type model. The full bent‐hyperbola model can accommodate both threshold and nonthreshold behavior, can take on concave up and concave down shapes with various levels of curvature, can approximate the biochemically relevant Michaelis–Menten model, and even be reduced to a straight line. Therefore, with the use of this model, the presence or absence of a threshold may even become irrelevant and the best fit of the full bent‐hyperbola model be used to characterize the dose–response behavior and risk levels, with no need for mode of action (MOA) information. Point of departure (POD), characterized by exposure level at which some predetermined response is reached, can be defined using the full model or one of the better fitting reduced models.     

Risk–Risk Tradeoff Analysis of Nuclear Explosives for Asteroid Deflection

To prevent catastrophic asteroid–Earth collisions, it has been proposed to use nuclear explosives to deflect away earthbound asteroids. However, this policy of nuclear deflection could inadvertently increase the risk of nuclear war and other violent conflict. This article conducts risk–risk tradeoff analysis to assess whether nuclear deflection results in a net increase or decrease in risk. Assuming nonnuclear deflection options are also used, nuclear deflection may only be needed for the largest and most imminent asteroid collisions. These are low‐frequency, high‐severity events. The effect of nuclear deflection on violent conflict risk is more ambiguous due to the complex and dynamic social factors at play. Indeed, it is not clear whether nuclear deflection would cause a net increase or decrease in violent conflict risk. Similarly, this article cannot reach a precise conclusion on the overall risk–risk tradeoff. The value of this article comes less from specific quantitative conclusions and more from providing an analytical framework and a better overall understanding of the policy decision. The article demonstrates the importance of integrated analysis of global risks and the policies to address them, as well as the challenge of quantitative evaluation of complex social processes such as violent conflict.     

竞争和风险规避对双渠道供应链决策的影响

针对具有风险规避特征的制造商和零售商组成的双渠道供应链,分析非竞争环境下双渠道供应链中产品在不同渠道的最优定价;研究存在替代产品竞争的市场环境下,原双渠道供应链中风险规避型参与者的定价决策以及替代产品决策者的最优定价;探讨双渠道中参与者的风险规避度对其定价决策的影响,分析表明随着参与者风险规避度的增大,供应链中各渠道的最优定价都减小,制造商和零售商的期望收益也随之减小;借助数值分析,研究竞争对风险规避型参与者决策的影响,并对模型中各关键参数进行敏感度分析。研究结果表明,一定程度的市场竞争会减弱参与者风险规避特征对其决策产生的影响,提高参与者的定价,增加参与者的收益。在参数的敏感度分析中,用来反映替代产品对双渠道上产品影响的交叉敏感度的增大会提高双渠道上产品的定价,也增加风险规避型参与者的收益。     

A Model of Delegated Project Choice

We present a model in which a principal delegates the choice of project to an agent with different preferences. The principal determines the set of projects from which the agent may choose. The principal can verify the characteristics of the project chosen by the agent, but does not know which other projects were available to the agent. We consider situations where the collection of available projects is exogenous to the agent but uncertain, where the agent must invest effort to discover a project, where the principal can pay the agent to choose a desirable project, and where the principal can adopt more complex schemes than simple permission sets.     

Addressing Supply–Demand Imbalance: Designing Efficient Remanufacturing Strategies

The management of remanufacturing inventory system is often challenged by mismatched supply (i.e., returned units, called cores) and demand. Typically, the demand for remanufactured units is high and exceeds the supply early in a product's lifetime, and drops below the supply late in the lifetime. This supply–demand imbalance motivates us to study a switching strategy to facilitate the decision‐making process. This strategy deploys a push mode at the early stage of a product's lifetime, which remanufactures scarce cores to stock to responsively satisfy the high demand, and switches to a pull mode as the product approaches obsolescence to accurately match the low demand with supply. In addition, the strategy further simplifies the decision‐making process by ignoring the impact of leftover cores at the end of each decision period. We show that the optimal policy of the switching strategy possesses a simple, multi‐dimensional base‐stock structure, which aims to remanufacture units from the i best‐quality categories up to the ith state‐independent base‐stock level. An extensive numerical study shows that the switching strategy delivers close‐to‐optimal and robust performance: the strategy only incurs an average profit loss of 1.21% and a maximum of 2.27%, compared with the optimal one. The numerical study also shows when a pure push or pull strategy, a special case of the switching strategy, delivers good performance. The study offers the managerial insight that firms can use simple, easy‐to‐implement strategies to efficiently manage the remanufacturing inventory system.     

Defender–Attacker Decision Tree Analysis to Combat Terrorism

We propose a methodology, called defender–attacker decision tree analysis, to evaluate defensive actions against terrorist attacks in a dynamic and hostile environment. Like most game‐theoretic formulations of this problem, we assume that the defenders act rationally by maximizing their expected utility or minimizing their expected costs. However, we do not assume that attackers maximize their expected utilities. Instead, we encode the defender's limited knowledge about the attacker's motivations and capabilities as a conditional probability distribution over the attacker's decisions. We apply this methodology to the problem of defending against possible terrorist attacks on commercial airplanes, using one of three weapons: infrared‐guided MANPADS (man‐portable air defense systems), laser‐guided MANPADS, or visually targeted RPGs (rocket propelled grenades). We also evaluate three countermeasures against these weapons: DIRCMs (directional infrared countermeasures), perimeter control around the airport, and hardening airplanes. The model includes deterrence effects, the effectiveness of the countermeasures, and the substitution of weapons and targets once a specific countermeasure is selected. It also includes a second stage of defensive decisions after an attack occurs. Key findings are: (1) due to the high cost of the countermeasures, not implementing countermeasures is the preferred defensive alternative for a large range of parameters; (2) if the probability of an attack and the associated consequences are large, a combination of DIRCMs and ground perimeter control are preferred over any single countermeasure.     

Solving the Feldstein–Horioka Puzzle With Financial Frictions

Unlike the prediction of a frictionless open economy model, long‐term average savings and investment rates are highly correlated across countries—a puzzle first identified by Feldstein and Horioka (1980). We quantitatively investigate the impact of two types of financial frictions on this correlation. One is limited enforcement, where contracts are enforced by the threat of default penalties. The other is limited spanning, where the only asset available is noncontingent bonds. We find that the calibrated model with both frictions produces a savings–investment correlation and a volume of capital flows close to the data. To solve the puzzle, the limited enforcement friction needs low default penalties under which capital flows are much lower than those in the data, and the limited spanning friction needs to exogenously restrict capital flows to the observed level. When combined, the two frictions interact to endogenously restrict capital flows and thereby solve the Feldstein–Horioka puzzle.