考虑制造商创新的供应链双向需求信息共享研究

本文考虑制造商创新,研究由一个制造商和一个零售商组成的两级供应链双向需求信息共享问题。制造商与零售商均拥有部分需求信息,且制造商进行成本降低创新,根据逆向分析求解方法分析制造商与零售商在均不共享、制造商单方共享、零售商单方共享、相互共享需求信息情形下的均衡决策,并分别通过求解制造商和零售商的事前利润来探讨制造商与零售商的需求信息共享价值。研究发现：制造商在四种需求信息共享情形下的创新投资增量均与获取的需求信息正相关,而与创新系数负相关。制造商的需求信息共享价值在制造商单方共享和互共享需求信息情形下总为负,在零售商单方共享情形下总为正。零售商的需求信息共享价值随着制造商创新能力的增强由负变正。本文在供应链双向需求信息共享的研究中引入制造商创新,拓展了相关研究,具有一定的理论价值和实践意义。     

The Law of Demand and Risk Aversion

This note proposes a necessary and sufficient condition on a utility function to guarantee that it generates a demand function satisfying the law of demand. This condition can be interpreted in terms of an agent's attitude towards lotteries in commodity space. As an application, we show that when an agent has an expected utility function, her demand for securities satisfies the law of demand if her coefficient of relative risk aversion does not vary by more than 4.     

对称信息下具有需求预测更新的供应链协调模型分析

针对传统预测与订货模式对不确定的需求缺乏反应的问题,建立了具有需求预测更新的订货模式模型,比较了两种订货模式在集中决策供应链中的收益和最优订货水平。而后针对分散决策供应链中具有需求预测更新的批发价合同引起的双重边际化问题,利用收入分配合同进行分析并得到解决方案及一些有用的结论。     

非对称信息下市场需求与生产成本同时发生扰动时的供应链决策

对由一个生产商和一个销售商组成的两级供应链模型,基于以生产商为主导的Stackelberg 博弈,针对需求函数分别为线性和非线性的情形,研究非对称信息下市场需求和生产成本同时扰动的供应链最优决策。在市场规模不确定的条件下建立生产商与销售商的利润函数,根据两类扰动之间的关系分四种情况确定供应链中各因素及总利润的最佳表示形式。通过数值仿真试验讨论供应链中各因素随扰动及市场信息变化而变化的各种趋势和最优生产量在一定条件下的鲁棒性,并进一步说明非对称信息下两类扰动对供应链的影响。     

Risk-Based Environmental Remediation: Bayesian Monte Carlo Analysis and the Expected Value of Sample Information

A methodology that simulates outcomes from future data collection programs, utilizes Bayesian Monte Carlo analysis to predict the resulting reduction in uncertainty in an environmental fate-and-transport model, and estimates the expected value of this reduction in uncertainty to a risk-based environmental remediation decision is illustrated considering polychlorinated biphenyl (PCB) sediment contamination and uptake by winter flounder in New Bedford Harbor, MA. The expected value of sample information (EVSI), the difference between the expected loss of the optimal decision based on the prior uncertainty analysis and the expected loss of the optimal decision from an updated information state, is calculated for several sampling plan. For the illustrative application we have posed, the EVSI for a sampling plan of two data points is $9.4 million, for five data points is $10.4 million, and for ten data points is $11.5 million. The EVSI for sampling plans involving larger numbers of data points is bounded by the expected value of perfect information, $15.6 million. A sensitivity analysis is conducted to examine the effect of selected model structure and parametric assumptions on the optimal decision and the EVSI. The optimal decision (total area to be dredged) is sensitive to the assumption of linearity between PCB sediment concentration and flounder PCB body burden and to the assumed relationship between area dredged and the harbor-wide average sediment PCB concentration; these assumptions also have a moderate impact on the computed EVSI. The EVSI is most sensitive to the unit cost of remediation and rather insensitive to the penalty cost associated with under-remediation.     

The Value of Improved National Exposure Information for Perchloroethylene (Perc): A Case Study for Dry Cleaners

Opportunities to improve our information about risk continue to arise and lead decision makers to indirectly address the issue of the value of improved information through resource allocation decisions. Statistical decision analysis techniques provide an analytical framework for valuing information explicitly in the context of regulatory decision making. This paper provides estimates of the value of improved national estimates of perchloroethylene (perc) exposure from U.S. dry cleaners in the context of EPA's recently promulgated National Emissions Standard for Hazardous Air Pollutants (NESHAP) with emphasis on exposure information. Consistent with the NESHAP decision, we relied on EPA's technology and economic assessments. In this first cut analysis, estimates of the exposures of workers, consumers of dry cleaning services, and the general public are probabilistically characterized to reflect uncertainty about exposure and potency. We consider the net benefits of the different control options by assessing the associated changes in the total annual population risks and valuing them in monetary terms, with no constraints placed on maximum individual risks. The results suggest that the expected value of perfect information (EVPI) about potency exceeds the EVPI about exposure. Sensitivity analyses demonstrate how the choices of the valuation parameters and distributions used to characterize uncertainty in the model affect the estimates of the value of information.     

Comment on “The Law of Large Demand for Information”

Say that one information structure is eventually Blackwell sufficient for another if, for every large enough n, an n‐sample from the first is Blackwell sufficient (Blackwell (1951, 1954)) for an n‐sample from the second. This note shows that eventual Blackwell sufficiency lies strictly between (one‐shot) Blackwell sufficiency and the ordering of information structures formulated by Moscarini and Smith (2002), and thus offers a new criterion for comparing experiments. A characterization of eventual Blackwell sufficiency in terms of the one‐shot experiments remains an open question.     

The Economic Value of Market Information for Farmers in Developing Economies

In developing countries, farmers lack information for making informed production, manufacturing/selling decisions to improve their earnings. To alleviate poverty, various non‐governmental organizations (NGOs) and for‐profit companies have developed different ways to distribute information about market price, crop advisory and farming technique to farmers. We investigate a fundamental question: will information create economic value for farmers? We construct a stylized model in which farmers face an uncertain market price (demand) and must make production decisions before the market price is realized. Each farmer has an imprecise private signal and an imprecise public signal to estimate the actual market price. By examining the equilibrium outcomes associated with a Cournot competition game, we show that private signals do create value by improving farmers' welfare. However, this value deteriorates as the public signal becomes available (or more precise). In contrast, in the presence of private signals, the public signal does not always create value for the farmers. Nevertheless, both private and public signals will reduce price variation. We also consider two separate extensions that involve non‐identical private signal precisions and farmers' risk‐aversion, and we find that the same results continue to hold. More importantly, we find that the public signal can reduce welfare inequality when farmers have non‐identical private signal precisions. Also, risk‐aversion can dampen the value created by private or public information.     

Managing the Reverse Channel with RFID‐Enabled Negative Demand Information

We analyze the inventory decisions of a manufacturer who has ample production capacity and also uses returned products to satisfy customer demand. All returned items go through an evaluation process, at the end of which the decision of disposal, direct reselling, or rework is made for each unit according to a predetermined procedure. We quantify the value of information/visibility on the reverse channel for the manufacturer by making comparisons among three approaches: No information‐naive; no visibility‐enlightened; and full visibility. We find the value of visibility increases with the comparative length of the reverse channel and volume, volatility, and usability of returns. Furthermore, the smarter the manufacturer, the less benefit visibility brings to the system. By this analysis, we quantify the visibility savings of radio frequency identification (RFID) in the reverse channel as a candidate enabler technology. We also provide numerical examples to show that practical approximations in inventory management may have acceptable penalties to the manufacturer with visibility.     

时间价格敏感型需求下的供应链决策模式研究

在定制产品的市场竞争中,需求不仅对价格敏感,对时间也十分敏感.本文以一个两阶段的供应链系统为背景,研究了分散决策和集中决策两种模式下的MTO供应链决策问题.分别分析了两种模式下的决策过程,进行了优化求解.并结合一个汽车行业定制供应链实例进行了数值分析,证明了对于时间价格敏感型需求下的供应链决策问题,集中决策模式能够实现更大的供应链整体收益.这些研究工作为供应链企业在时间价格敏感型市场上竞争提供了有效的决策工具和方法.     

The Value of Information for Managing Retail Inventory Remotely

An important difference between both manufacturing and wholesaling vs. retail is the information available concerning inventory. Typically, far less information characterizes retail. Here, an extreme environment of information shortfall is examined. The environment is technically termed “unattended points of sale,” but colloquially called vending machines. Once inventory is loaded into a machine, information on demand and inventory level is not observed until the scheduled reloading date. Technological advances and business process changes have drawn attention to the value of information (VOI) in retail inventory in many venues. Moreover, technology is now available that allows unattended points of sale to report inventory information. Capturing the value of this information requires changes in current business practice. We demonstrate the value of capturing information analytically in an environment with restrictive demand assumptions. Experiments in an environment with realistic demand assumptions and parameter values show that the VOI depends greatly on operating characteristics and can range from negligible effects to increasing profitability 30% or more in actual practice.     

需求不确定下制造商服务投入影响销售的供应链信息共享与激励

针对需求不确定环境下制造商既提供产品也提供相关服务时产品服务供应链中的信息共享与激励问题,考虑零售商拥有需求预测信息且可选择共享任意水平的信息量,通过构建不完全信息下的动态博弈模型,分析了零售商信息共享水平、制造商服务效率以及消费者服务敏感性对服务价值和信息共享价值的影响,并提出了基于两部补偿契约的信息共享激励策略。研究表明：需求信息共享能够有效提升整个供应链的服务价值;当制造商服务效率或者消费者服务敏感性较高时,信息共享的服务改善效应将占优于其双边际效应,零售商会自愿共享全部需求信息并达到供应链"双赢";而当制造商服务效率或者消费者服务敏感性较低时,采用两部补偿激励契约可实现产品服务供应链中的完全信息共享,并且契约实施难度会随着零售商需求预测精度、制造商服务效率以及消费者服务敏感性的提高而降低。     

The Value of Environmental Information without Control of Subsequent Decisions

The standard value of information approach of decision analysis assumes that the individual or agency that collects the information is also in control of the subsequent decisions based on the information. We refer to this situation as the “value of information with control (VOI‐C).” This paradigm leads to powerful results, for example, that the value of information cannot be negative and that it is zero, when the information cannot change subsequent decisions. In many real world situations, however, the agency collecting the information is different from the one that makes the decision on the basis of that information. For example, an environmental research group may contemplate to fund a study that can affect an environmental policy decision that is made by a regulatory organization. In this two‐agency formulation, the information‐acquiring agency has to decide, whether an investment in research is worthwhile, while not being in control of the subsequent decision. We refer to this situation as “value of information without control (VOI‐NC).” In this article, we present a framework for the VOI‐NC and illustrate it with an example of a specific problem of determining the value of a research program on the health effects of power‐frequency electromagnetic fields. We first compare the VOI‐C approach with the VOI‐NC approach. We show that the VOI‐NC can be negative, but that with high‐quality research (low probabilities of errors of type I and II) it is positive. We also demonstrate, both in the example and in more general mathematical terms, that the VOI‐NC for environmental studies breaks down into a sum of the VOI‐NC due to the possible reduction of environmental impacts and the VOI‐NC due to the reduction of policy costs, with each component being positive for low environmental impacts and high‐quality research. Interesting results include that the environmental and cost components of the VOI‐NC move in opposite directions as a function of the probability of environmental impacts and that VOI‐NC can be positive, even though the probability of environmental impacts is zero or one.     

基于不对称需求信息的供应链最小订购量决策

在由一个供应商和一个零售商组成的两级分散供应链中,供应商通过制定最小订购量取得规模效应,保障自身利益。当零售商和供应商之间存在需求信息不对称时,即零售商掌握需求信息而供应商仅知道需求信息中价格敏感因子的分布,如何进行最小订购量决策成为供应商面临的一个重要问题。针对这一问题,从营销视角构建了基于Stackelberg博弈的利润最大化模型。假设供应商知道需求的价格敏感因子服从正态分布,通过严密的数学推导确定了模型中的最优最小订购量。将提出的最优最小订购量决策方法应用于云存储的销售供应链中,确定了云存储供应商销售的最优最小存储容量,阐释了方法的合理性与有效性。通过实验研究发现,最小订购量的设置提升了供应商的利润。所提方法对于考虑最小订购量的供应链协调研究具有积极的推动作用。     

The Impact of External Demand Information on Parallel Supply Chains with Interacting Demand

This paper considers two parallel supply chains with interacting demand streams. Each supply chain consists of one supplier and one retailer. The two demand streams are jointly described with a vector autoregressive time‐series process in which they interact and their respective innovation errors correlate contemporaneously. For each supply chain, we develop insights into when and how much the supplier and the retailer can improve on their forecasting accuracy if the external demand history of the other supply chain is utilized. When this external demand history is not available or made available after a time lag, we develop a partial process and a delayed process to characterize the demand structure that the retailer can recover from the available demand histories. Our results show that the external demand history of the other supply chain always helps the retailer make better forecasts when demand streams interact; however, the enhanced information alters the retailer's order process, which may produce larger forecasting errors for the supplier. Conditions are established for the supplier to benefit from the external demand history of the other supply chain.     

Estimation of Error and Bias in Bayesian Monte Carlo Decision Analysis Using the Bootstrap

Bayesian Monte Carlo (BMC) decision analysis adopts a sampling procedure to estimate likelihoods and distributions of outcomes, and then uses that information to calculate the expected performance of alternative strategies, the value of information, and the value of including uncertainty. These decision analysis outputs are therefore subject to sample error. The standard error of each estimate and its bias, if any, can be estimated by the bootstrap procedure. The bootstrap operates by resampling (with replacement) from the original BMC sample, and redoing the decision analysis. Repeating this procedure yields a distribution of decision analysis outputs. The bootstrap approach to estimating the effect of sample error upon BMC analysis is illustrated with a simple value-of-information calculation along with an analysis of a proposed control structure for Lake Erie. The examples show that the outputs of BMC decision analysis can have high levels of sample error and bias.     

首席信息官评估信息服务价值的行为与决策研究

本文是针对企业在IT投资决策过程中评估信息服务价值的理论和实证研究。首先通过发放问卷,调研了中国信息技术密集型企业IT投资的决策环境和首席信息官(Chief Information Officer,简称CIO)的风险态度。其次,在调研结论的基础上,利用贝叶斯决策理论,建立CIO评估外部信息服务价值的数学模型。实证调研表明,在IT投资决策过程中,大部分CIO属于风险中性。针对风险中性的决策者,本文分析了购买信息服务所规避损失或者增加收益的期望值,并与信息服务的费用进行比较,以帮助CIO做出是否购买信息服务和是否进行IT投资的决策。在应用案例中,对一家大型电子商务企业进行了实地调研,并对访谈资料和文档数据进行分析。应用案例的分析结果表明:本文的研究结论适用于中国信息技术密集型企业,能够提供相关决策的依据。     

Tiered Chemical Testing: A Value of Information Approach

In December 2000 the EPA initiated the Voluntary Children's Chemical Evaluation Program (VCCEP) by asking manufacturers to voluntarily sponsor toxicological testing in a tiered process for 23 chemicals selected for the pilot phase. The tiered nature of the VCCEP pilot program creates the need for clearly defined criteria for determining when information is sufficient to assess the potential risks to children. This raises questions about how to determine the "adequacy" of the existing information and assess the need to undertake efforts to reduce uncertainty (through further testing). This article applies a value of information analysis approach to determine adequacy by modeling how toxicological and exposure data collected through the VCCEP may be used to inform risk management decisions. The analysis demonstrates the importance of information about the exposure level and control costs in making decisions regarding further toxicological testing. This article accounts for the cost of delaying control action and identifies the optimal testing strategy for a constrained decisionmaker who, absent applicable human data, cannot regulate without bioassay data on a specific chemical. It also quantifies the differences in optimal testing strategy for three decision criteria: maximizing societal net benefits, ensuring maximum exposure control while net benefits are positive (i.e., benefits outweigh costs), and controlling to the maximum extent technologically feasible while the lifetime risk of cancer exceeds a specific level of risk. Finally, this article shows the large differences that exist in net benefits between the three criteria for the range of exposure levels where the optimal actions differ.     

The Value of Information in Decision‐Analytic Modeling for Malaria Vector Control in East Africa

Decision analysis tools and mathematical modeling are increasingly emphasized in malaria control programs worldwide to improve resource allocation and address ongoing challenges with sustainability. However, such tools require substantial scientific evidence, which is costly to acquire. The value of information (VOI) has been proposed as a metric for gauging the value of reduced model uncertainty. We apply this concept to an evidenced‐based Malaria Decision Analysis Support Tool (MDAST) designed for application in East Africa. In developing MDAST, substantial gaps in the scientific evidence base were identified regarding insecticide resistance in malaria vector control and the effectiveness of alternative mosquito control approaches, including larviciding. We identify four entomological parameters in the model (two for insecticide resistance and two for larviciding) that involve high levels of uncertainty and to which outputs in MDAST are sensitive. We estimate and compare a VOI for combinations of these parameters in evaluating three policy alternatives relative to a status quo policy. We find having perfect information on the uncertain parameters could improve program net benefits by up to 5–21%, with the highest VOI associated with jointly eliminating uncertainty about reproductive speed of malaria‐transmitting mosquitoes and initial efficacy of larviciding at reducing the emergence of new adult mosquitoes. Future research on parameter uncertainty in decision analysis of malaria control policy should investigate the VOI with respect to other aspects of malaria transmission (such as antimalarial resistance), the costs of reducing uncertainty in these parameters, and the extent to which imperfect information about these parameters can improve payoffs.