非对称信息下双渠道供应链的定价决策

探讨在零售商的风险规避度分别为完全信息和私有信息2种情况下的供应链决策问题,比较2种情况下的最优决策值发现：制造商的直销渠道价格不受风险规避度是否信息私有的影响。制造商的最优批发价格和零售商的最优零售渠道价格随制造商掌握的风险规避度均值的变化而变化。数值算例验证了该结论,并计算存在直销渠道价格不能小于批发价格约束时的最优决策值。通过对无约束和有约束情况下最优决策值的比较表明：虽然2种情况下产品的市场销售总量不变,但约束条件的存在能够减弱直销渠道对传统零售渠道的影响。     

属性值为区间数的多属性决策对象排序研究

多属性决策问题的实质利用已有决策信息,通过一定方式对备选方案进行排序和择优。针对属性值为区间数的多属性决策对象排序问题,首先,提出决策对象优势关系这一概念,再次,得出决策对象的优势关系与其属性值两端点的实数值之和存在等价关系;最后,利用属性值为区间数的多属性决策实例对该算法进行了实例分析,并利用优势关系对决策对象进行排序并择优。     

Farmers’ Risk‐Based Decision Making Under Pervasive Uncertainty: Cognitive Thresholds and Hazy Hedging

Researchers in judgment and decision making have long debunked the idea that we are economically rational optimizers. However, problematic assumptions of rationality remain common in studies of agricultural economics and climate change adaptation, especially those that involve quantitative models. Recent movement toward more complex agent‐based modeling provides an opportunity to reconsider the empirical basis for farmer decision making. Here, we reconceptualize farmer decision making from the ground up, using an in situ mental models approach to analyze weather and climate risk management. We assess how large‐scale commercial grain farmers in South Africa (n = 90) coordinate decisions about weather, climate variability, and climate change with those around other environmental, agronomic, economic, political, and personal risks that they manage every day. Contrary to common simplifying assumptions, we show that these farmers tend to satisfice rather than optimize as they face intractable and multifaceted uncertainty; they make imperfect use of limited information; they are differently averse to different risks; they make decisions on multiple time horizons; they are cautious in responding to changing conditions; and their diverse risk perceptions contribute to important differences in individual behaviors. We find that they use two important nonoptimizing strategies, which we call cognitive thresholds and hazy hedging, to make practical decisions under pervasive uncertainty. These strategies, evident in farmers' simultaneous use of conservation agriculture and livestock to manage weather risks, are the messy in situ performance of naturalistic decision‐making techniques. These results may inform continued research on such behavioral tendencies in narrower lab‐ and modeling‐based studies.     

Understanding Community Resilience from a PRA Perspective Using Binary Decision Diagrams

Probabilistic risk assessment (PRA) is a useful tool to assess complex interconnected systems. This article leverages the capabilities of PRA tools developed for industrial and nuclear risk analysis in community resilience evaluations by modeling the food security of a community in terms of its built environment as an integrated system. To this end, we model the performance of Gilroy, CA, a moderate‐size town, with regard to disruptions in its food supply caused by a severe earthquake. The food retailers of Gilroy, along with the electrical power network, water network elements, and bridges are considered as components of a system. Fault and event trees are constructed to model the requirements for continuous food supply to community residents and are analyzed efficiently using binary decision diagrams (BDDs). The study also identifies shortcomings in approximate classical system analysis methods in assessing community resilience. Importance factors are utilized to rank the importance of various factors to the overall risk of food insecurity. Finally, the study considers the impact of various sources of uncertainties in the hazard modeling and performance of infrastructure on food security measures. The methodology can be applicable for any existing critical infrastructure system and has potential extensions to other hazards.     

Linking Decision Theory and Quantitative Microbial Risk Assessment: Tradeoffs Between Compliance and Efficacy for Waterborne Disease Interventions

Achieving health gains from the U.N. Sustainable Development Goals of universal coverage for water and sanitation will require interventions that can be widely adopted and maintained. Effectiveness—how an intervention performs based on actual use—as opposed to efficacy will therefore be central to evaluations of new and existing interventions. Incomplete compliance—when people do not always use the intervention and are therefore exposed to contamination—is thought to be responsible for the lower‐than‐expected risk reductions observed from water, sanitation, and hygiene interventions based on their efficacy at removing pathogens. We explicitly incorporated decision theory into a quantitative microbial risk assessment model. Specifically, we assume that the usability of household water treatment (HWT) devices (filters and chlorine) decreases as they become more efficacious due to issues such as taste or flow rates. Simulations were run to examine the tradeoff between device efficacy and usability. For most situations, HWT interventions that trade lower efficacy (i.e., remove less pathogens) for higher compliance (i.e., better usability) contribute substantial reductions in diarrheal disease risk compared to devices meeting current World Health Organization efficacy guidelines. Recommendations that take into account both the behavioral and microbiological properties of treatment devices are likely to be more effective at reducing the burden of diarrheal disease than current standards that only consider efficacy.     

Assessing Engineering Resilience for Systems with Multiple Performance Measures

Recently, efforts to model and assess a system's resilience to disruptions due to environmental and adversarial threats have increased substantially. Researchers have investigated resilience in many disciplines, including sociology, psychology, computer networks, and engineering systems, to name a few. When assessing engineering system resilience, the resilience assessment typically considers a single performance measure, a disruption, a loss of performance, the time required to recover, or a combination of these elements. We define and use a resilient engineered system definition that separates system resilience into platform and mission resilience. Most complex systems have multiple performance measures; this research proposes using multiple objective decision analysis to assess system resilience for systems with multiple performance measures using two distinct methods. The first method quantifies platform resilience and includes resilience and other “ilities” directly in the value hierarchy, while the second method quantifies mission resilience and uses the “ilities” in the calculation of the expected mission performance for every performance measure in the value hierarchy. We illustrate the mission resilience method using a transportation systems‐of‐systems network with varying levels of resilience due to the level of connectivity and autonomy of the vehicles and platform resilience by using a notional military example. Our analysis found that it is necessary to quantify performance in context with specific mission(s) and scenario(s) under specific threat(s) and then use modeling and simulation to help determine the resilience of a system for a given set of conditions. The example demonstrates how incorporating system mission resilience can improve performance for some performance measures while negatively affecting others.     

哪些创业失败者更可能卷土重来?———基于松 － 紧文化与制度环境的跨国比较研究

高失败率是创业热潮中创业者必须面对的基本事实.创业失败在为创业者带来大量情绪与财务成本的同时,也提供了独特的学习经验.如何激活创业失败者卷土重来的激情是降低创业社会成本的关键.文章整合组织学习和创业认知理论构建了统一的创业失败学习理论逻辑,结合全球创业观察(Global Entrepreneurship Monitor)、世界银行和松-紧文化3个跨国数据库,考察了不同国家文化与制度环境下不同性别个体的创业失败经历对其创业选择的影响.研究发现:与没有失败经历的个体相比,有创业失败经历的个体更可能选择创业;高宽松度的国家文化、好的制度环境分别强化了这一关系;性别与文化宽松度对这一关系有显著的三重调节效应.即在高宽松度的国家文化下,有创业失败经历的女性创业者再次创业的概率更高.将性别角色差异纳入到创业失败的分析框架中,同时也扩展了创业失败的文化与制度分析.     

基于多目标加权灰靶决策模型的节能服务公司选择研究

用能方对节能服务公司（Energy Service Company,ESCO）的选择关系到合同能源管理（Energy Performance Contracting,EPC）能否顺利实施。从用能方的角度,采用灰色系统理论中的多目标加权灰靶决策模型,对存在多决策目标的ESCO选择问题进行研究。通过层次分析法确定ESCO的11个决策目标的决策权数,根据综合效果测度值的比较,最终实现最优对策的选择。本文为用能方的ESCO选择问题提供了一种新的思路。     

基于混合加权距离的毕达哥拉斯模糊TOPSIS多属性决策方法研究

针对决策信息为毕达哥拉斯模糊集的多属性决策问题,提出了一种基于混合加权测度的TOPSIS决策方法。在分析了现有距离测度方法不足的基础上,首先给出了一种新的毕达哥拉斯模糊距离测度——毕达哥拉斯模糊有序加权距离（PFOWD）,并研究了该测度权重的确定方法;在PFOWD基础上,进一步提出了毕达哥拉斯模糊混合加权距离（PFHWD）,同时探讨了其特征和与现有毕达哥拉斯模糊测度的关系;最后提出了一种基于PFHWD测度的毕达哥拉斯模糊TOPSIS多属性方法,并用实例验证了方法的有效性和可行性。     

体验型产品消费行为的羊群效应及机理研究——基于电影行业消费行为的实证解释

互联网环境下消费者购买体验型产品时对网络信息的依赖性很大。因此,研究社交媒体影响下体验型产品的消费者决策选择行为具有现实意义。本文以电影行业的票房偏离及消费跟风现象为切入点,探究体验型产品的羊群效应并对其产生的内在机理进行解释。采集艺恩资讯的票房数据以及豆瓣的电影基本信息及影评等数据作为研究样本,从消费者"羊群行为"视角分析其对电影票房的影响。研究发现：在控制了质量等内生性影响之后,消费者羊群效应依然存在;产品特征信息对羊群效应起到了调节作用,从而形成理性跟随;采用预期差异模型可以解释消费者实现理性跟随的过程。研究结论对于电影行业宏观政策制定及对体验型产品合理进行营销推广提供了理论基础与实证依据。